A Review of Three Recently Published Papers on Dietary Approaches to Weight Loss and Fat Mobilization

A Review of Three Recently Published Papers on Dietary Approaches to Weight Loss and Fat Mobilization

By Kristen N Smith, PhD, RD; Mary R Dicklin, PhD; Kevin C Maki, PhD, CLS



There have been multiple papers published this year focusing on various dietary approaches for producing weight loss and their effects on weight-related outcomes, including changes in body composition and cardiovascular disease risk factors. This post will summarize three recently published original research articles.


  1. Low-Fat vs. Low-Carbohydrate and Weight-Loss Diets (DIETFITS)1:

It is well-established that obesity is a major public health challenge and that dietary modifications are essential for successful weight loss. Commonly investigated approaches include diets that restrict intake of fat or carbohydrate2-4. No matter what macronutrient is emphasized or restricted, most trials have reported modest (~ 5% or less) mean weight loss after 12 months, with negligible differences between the different diet groups.5 However, when assessing weight-loss outcomes of individual subjects, these have varied widely within diet groups and ranged from weight loss of ~25 kg (~55 lbs) to weight gain of ~5 kg (11 lbs).2-4 There appears to be no one specific dietary strategy that is consistently superior for weight management within the general population. Additionally, results from some prior studies have suggested that an individual’s genotype or insulin-glucose dynamics may have an impact on the outcomes associated with certain diets. For example, it has been hypothesized that individuals with higher insulin resistance or insulin secretion may respond more favorably to a low-carbohydrate dietary regimen.6


The objective of the Diet Intervention Examining the Factors Interacting with Treatment Success (DIETFITS) trial was to assess the effect of a healthy low-fat (HLF) diet vs. a healthy low-carbohydrate (HLC) diet on weight change and to examine whether genotype pattern or insulin secretion are related to dietary effects on weight loss. This study was a single-site, parallel-group, weight-loss trial that randomized individuals to either a HLF diet or a HLC diet for 12 months. Subjects (N = 609) were men and premenopausal women aged 18 to 50 y with body mass index (BMI) 28 to 40 kg/m2. The study began with a 1-month run-in during which subjects were instructed to maintain their habitual diet, physical activity and body weight. Throughout the study period, registered dietitian health educators led 22 diet-specific instructional sessions guiding the participants to follow their assigned plan. The researchers also investigated whether three single-nucleotide polymorphism multi-locus genotype patterns or insulin secretion (blood concentration of insulin 30 min after a glucose challenge) were associated with weight loss.


Primary Outcome

Secondary Outcomes

§  12-month weight change

§  Other anthropometric measures (BMI, % body fat, waist circumference)

§  Plasma lipids

§  Plasma insulin and glucose (fasting and after a glucose challenge)

§  Blood pressure


Subject characteristics:

  • Mean (standard deviation) age: 40 (7) y,
  • 57% women,
  • Mean (standard deviation) BMI: 33 (3) kg/m2,
  • Mean baseline blood concentration of insulin 30 min after glucose challenge 93 µU/mL,
  • 481 (79%) completed the trial.


Weight change at 12 months did not vary between the two diet groups (-5.3 kg for HLF vs -6.0 kg for HLC; mean between-group difference, 0.7 kg 95% confidence interval, -0.2 to 1.6 kg). There were no significant diet x genotype (p = 0.20) or diet x insulin secretion interactions (p = 0.47). Overall, both diets produced a mean weight loss of ~6 kg over 12 months, but no new knowledge was gained regarding how to identify which diet would be better suited for whom.


  1. Vegetarian vs. Mediterranean Diet and Cardiovascular Disease Risk (CARDIVEG)7:

A lacto-ovo vegetarian diet (VD) is the most common type of vegetarian diet. It excludes meat, fish and poultry in all forms, but allows intake of eggs and dairy products.8 A 2017 meta-analysis of >130,000 vegetarians found that adherence to a VD was associated with many favorable health characteristics, including lower levels of cardiovascular disease risk factors and reduced risk for ischemic heart disease.9 The potential health benefits associated with a VD may require additional investigation for several reasons: most of the studies on VD were 1) observational, 2) conducted in countries at high risk for cardiovascular disease (like the United States), 3) conducted in people who were already vegetarians. These are possible sources of bias because populations already following vegetarian patterns may be more health conscious and not fully representative of the overall population.10 Consequently, additional investigation of healthy VD and omnivorous patterns is warranted.


The aim of the Cardiovascular Prevention with Vegetarian Diet (CARDIVEG) study was to compare, in an omnivorous, low-cardiovascular-risk European population, the effects of a 3-month period on a VD versus a low-calorie Mediterranean diet (MedD) on markers of cardiovascular disease risk.11 It is important to note that the MedD is often reported as one of the healthiest models for preventing cardiovascular disease.12  The study was a randomized, open, crossover trial with 2 intervention periods of VD or MedD, each lasting 3 months, after an initial 2-week run-in period to assess participants’ motivation, commitment and availability.11 Participants underwent face-to-face, individual counseling sessions where they also received 1-week menu plans. Both interventions were low-calorie in nature and aimed at reducing body weight and risk factors for cardiovascular disease.


Both diet plans consisted of ~50-55% energy from carbohydrate, ~25-30% energy from total fat (≤7% energy from saturated fat, <200 mg cholesterol), and ~15-20% energy from protein. The VD was characterized by abstinence from consumption of meat and meat products, poultry, fish and seafood, and the flesh of any other animal, but it included eggs and dairy products and all other food groups. The MedD was characterized by consumption of all food groups, including meat and meat products, poultry and fish.


Primary Outcomes

Secondary Outcomes

Changes from baseline in:

§  Total body weight

§  BMI

§  Fat mass

Changes from baseline in:

§  Circulating cardiovascular risk parameters

o   Lipid profile

o   Glycemic profile

o   Oxidative stress profile

o   Inflammatory profile


Of the 118 subjects randomized, 104 completed the VD period and 103 completed the MedD period. No differences were observed between the two diets in body weight. Similar outcomes were also reported for BMI and fat mass. However, responses in laboratory outcomes including low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), vitamin B12 and uric acid levels varied. The VD significantly produced significantly larger reductions in LDL-C, vitamin B12 and uric acid levels, whereas the MedD led to a significantly greater reduction in TG levels.


The authors concluded that both low-calorie diets contributed to weight loss to a similar degree and cardiovascular risk factor levels at the end of the two diet periods were similar, although LDL-C was slightly lower during the VD period and TG was slightly lower during the MedD period. These results provide further evidence that both the VD and MedD are useful options for weight loss and managing the cardiovascular risk factor profile.


  1. Lifestyle and Diet Strategies and Fat Mobilization (CENTRAL)13

Visceral adipose tissue (VAT) is the most strongly implicated fat storage pool connecting obesity to cardiometabolic disease risk. This may be attributed to the propensity of abdominal fat to activate obesity-related stress-sensing pathways14 and release secretory products and free fatty acids into the portal vein.15


Results from prior studies have been controversial regarding whether specific interventions can preferentially reduce VAT.16-20 Some studies have shown that dietary interventions did not preferentially impact abdominal fat depots,18,19 whereas others in both humans and in animal models suggest dietary changes might impact VAT, with higher intakes of simple sugars and trans fatty acids being associated with increased VAT, and higher intakes of unsaturated fatty acids associated with reductions in VAT. It is unclear whether lifestyle patterns and interventions can impact losses in specific fat depots (e.g., abdominal, pericardial, and renal sinus) and deposits (e.g., hepatic, intermuscular, and pancreatic), thus producing differential effects on the cardiometabolic risk factor profile.21 The objective of the CENTRAL trial was to test the hypothesis that, beyond long-term moderate weight loss, it is possible to induce differential mobilization of VAT and other specific fat depots by lifestyle interventions, and to link the changes to specific clinical biomarkers.


This was an 18-month randomized controlled trial of 278 sedentary men and women with abdominal obesity or dyslipidemia. Subjects were randomly assigned to either a low-fat (LF) diet or a Mediterranean/low-carbohydrate (MED/LC) diet. Both diets were designed for moderate, long-term weight loss and restricted intakes of refined carbohydrates and trans fats, and to have increased vegetable intakes. The LF diet had <30% of calories from total fat, ≤10% of calories from saturated fat and ≤200 mg/d cholesterol. The MED/LC diet had <40 g/d carbohydrate intake in the first 2 months, gradually increased to ≤70 g/d, and increased protein and fat intakes (rich in vegetables and legumes and low in red meat). Lunch was provided daily in a workplace cafeteria, and subjects received nutritional counseling periodically throughout the study. After 6 months of dietary intervention, each group was further randomized into added moderate physical activity (PA; 80% aerobic; supervised/free gym membership) or no added PA groups.


Primary Outcomes

Secondary Outcomes and Biomarker Measurements

§  Body fat redistribution (VAT)

§  Dynamics of different fat depots:

o   Deep and superficial subcutaneous

o   Liver

o   Pericardial

o   Muscle

o   Pancreas

o   Renal sinus

§  Lipid profile

§  Glycemic profile

§  Leptin

§  C-reactive protein


Although final weight loss was not different between dietary interventions, exercise reduced waist circumference with the greatest impact in the MED/LC/PA+ group (p<0.05). VAT (-22%), intrahepatic (-29%), and intrapericardial (-11%) fat reductions from baseline were greater than pancreatic and intramuscular fat declines. PA with either dietary intervention contributed to a significantly greater loss in VAT (mean of difference, -6.67 cm2; 95% CI, -14.8 to -0.45) compared with no PA. The MED/LC diet yielded greater reductions in intrahepatic, intrapericardial, and pancreatic fats (p<0.05 for all) compared with the LF diet. Renal sinus and femoral intramuscular fats were not preferentially impacted by one diet vs. the other.


The study outcomes described support dietary and PA interventions for weight loss as the goal.  It also appears that the MED/LC diet pattern was more effective than a LF diet for reducing storage of intrahepatic, intrapericardial and pancreatic fat, which may have long-term implications for effects on the cardiometabolic risk factor profile, although this needs to be verified. PA, regardless of diet, independently contributed to VAT loss.


Although both diets produced similar moderate weight loss, the MED/LC diet resulted in greater improvements in certain cardiometabolic risk factors, including greater reductions in waist circumference, TG and TG/high-density lipoprotein cholesterol ratio and increased high-density lipoprotein cholesterol. These changes remained significant after adjusting for weight loss.



No significant differences were noted in weight loss between the dietary interventions in the three studies reviewed, although some differences were noted in the effects of the different types of diets on cardiometabolic risk factors. It is no surprise that incorporating PA into the weight loss regimen enhanced reductions in VAT and intrahepatic fat. The take-away message seems to be that energy restricted low-fat, low-carbohydrate, or Mediterranean-style diet patterns can all be effective for promoting weight/fat loss and improving the cardiometabolic risk factor profile. Individual responses and personal preferences vary widely, and those attempting to lose weight and body fat can be reassured that it is acceptable to employ any of the energy restricted dietary patterns studied in these trials, particularly when combined with sufficient PA.



  1. Gardner CD, Trepanowski JF, Del Gobbo LC, et al. Effect of low-fat vs low-carbohydrate diet on 12-month weight loss in overweight adults and the association with genotype pattern or insulin secretion: The DIETFITS randomized clinical trial. JAMA. 2018;319(7):667-679.
  2. Gardner CD, Kiazand A, Alhassan S, et al. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A TO Z Weight Loss Study: a randomized trial. JAMA. 2007;297(9):969-977.
  3. Sacks FM, Bray GA, Carey VJ, et al. Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates. N Engl J Med. 2009;360(9):859-873.
  4. Shai I, Schwarzfuchs D, Henkin Y, et al. Weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. N Engl J Med. 2008;359(3):229-241.
  5. Johnston BC, Kanters S, Bandayrel K, et al. Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. JAMA. 2014;312(9):923-933.
  6. Fleming JA, Kris-Etherton PM. Macronutrient content of the diet: What do we know about energy balanace and weight maintenance. Curr Obes Rep. 2015;5(2):208-213.
  7. Sofi F, Dinu M, Pagliai G, et al. Low-calorie vegetarian versus mediterranean diets for reducing body weight and improving cardiovascular risk profile: CARDIVEG Study (Cardiovascular Prevention With Vegetarian Diet). Circulation. 2018;137(11):1103-1113.
  8. Leitzmann C. Vegetarian nutrition: past, present, future. Am J Clin Nutr. 2014;100 Suppl 1:496S-502S.
  9. Dinu M, Abbate R, Gensini GF, Casini A, Sofi F. Vegetarian, vegan diets and multiple health outcomes: A systematic review with meta-analysis of observational studies. Crit Rev Food Sci Nutr. 2017;57(17):3640-3649.
  10. Kwok CS, Umar S, Myint PK, Mamas MA, Loke YK. Vegetarian diet, Seventh Day Adventists and risk of cardiovascular mortality: a systematic review and meta-analysis. Int J Cardiol. 2014;176(3):680-686.
  11. Dinu M, Pagliai G, Casini A, Sofi F. Mediterranean diet and multiple health outcomes: an umbrella review of meta-analyses of observational studies and randomised trials. Eur J Clin Nutr. 2018;72(1):30-43.
  12. Sofi F, Dinu M, Pagliai G, Cesari F, Marcucci R, Casini A. Mediterranean versus vegetarian diet for cardiovascular disease prevention (the CARDIVEG study): study protocol for a randomized controlled trial. Trials. 2016;17(1):233.
  13. Gepner Y, Shelef I, Schwarzfuchs D, et al. Effect of distinct lifestyle interventions on mobilization of fat storage pools: CENTRAL Magnetic Resonance Imaging Randomized Controlled Trial. Circulation. 2018;137(11):1143-1157.
  14. Rudich A, Kanety H, Bashan N. Adipose stress-sensing kinases: linking obesity to malfunction. Trends Endocrinol Metab. 2007;18(8):291-299.
  15. Item F, Konrad D. Visceral fat and metabolic inflammation: the portal theory revisited. Obes Rev. 2012;13 Suppl 2:30-39.
  16. Rosqvist F, Iggman D, Kullberg J, et al. Overfeeding polyunsaturated and saturated fat causes distinct effects on liver and visceral fat accumulation in humans. Diabetes. 2014;63(7):2356-2368.
  17. Maersk M, Belza A, Stodkilde-Jorgensen H, et al. Sucrose-sweetened beverages increase fat storage in the liver, muscle, and visceral fat depot: a 6-mo randomized intervention study. Am J Clin Nutr. 2012;95(2):283-289.
  18. Bray GA, Smith SR, de Jonge L, et al. Effect of dietary protein content on weight gain, energy expenditure, and body composition during overeating: a randomized controlled trial. JAMA. 2012;307(1):47-55.
  19. Haufe S, Engeli S, Kast P, et al. Randomized comparison of reduced fat and reduced carbohydrate hypocaloric diets on intrahepatic fat in overweight and obese human subjects. Hepatology. 2011;53(5):1504-1514.
  20. Rokling-Andersen MH, Rustan AC, Wensaas AJ, et al. Marine n-3 fatty acids promote size reduction of visceral adipose depots, without altering body weight and composition, in male Wistar rats fed a high-fat diet. Br J Nutr. 2009;102(7):995-1006.
  21. Tchernof A, Despres JP. Pathophysiology of human visceral obesity: an update. Physiol Rev. 2013;93(1):359-404.


Photo by Joel Filipe

Differential Effects of n-3 and n-6 Fatty Acids on Carotid Plaque and Its Progression: Analyses from The Multi-Ethnic Study of Atherosclerosis

Differential Effects of n-3 and n-6 Fatty Acids on Carotid Plaque and Its Progression: Analyses from The Multi-Ethnic Study of Atherosclerosis

By Kristen N Smith, PhD, RD, LD; Mary R Dicklin, PhD; Kevin C Maki, PhD, CLS, FNLA


The process of atherosclerotic development is multifactorial involving inflammation, endothelial activation, oxidative stress and lipid accumulation in the arterial wall resulting in plaque accretion and vessel occlusion.1 Data have shown that atherogenesis can occur as early as adolescence2 and support the need for the identification and control of modifiable risk factors.  Long chain omega-3 (n-3) and omega-6 (n-6) polyunsaturated fatty acids (PUFAs) have been hypothesized to have antiatherogenic properties, yet the available evidence is inconsistent and no large multiethnic studies have examined n-3 and n-6 levels in plasma in relation to subclinical atherosclerosis outcomes.

Overall, n-3 PUFAs (including plant-derived alpha-linolenic acid [ALA] and fish oil eicosapentaenoic acid [EPA] and docosahexaenoic acid [DHA]) have been considered cardioprotective and their plasma concentrations inversely associated with inflammation and endothelial activation.3-8 Cohort studies have shown n-3 PUFAs to be associated with lower risk of cardiovascular outcomes.9,10 However, null results in recent meta-analyses and randomized controlled trials11-13 have raised questions regarding the benefits associated with n-3 FAs.

Compared to n-3 PUFAs, n-6 PUFAs have not been studied as thoroughly, but have been suggested by some to be proinflammatory and proatherogenic.14 This impression of n-6 PUFAs likely stemmed from the observation that the essential n-6 PUFA, linoleic acid (LA) can be converted to arachidonic acid (AA) – which is a substrate for eicosanoid lipid mediators that promote vascular disease.14,15 More recently this perception has been changing16 and results from observational studies suggest that LA and AA may both have cardiovascular benefits.6,17-19 Conversely, n-6 PUFAs such as gamma-linolenic acid and dihomo-gamma-linolenic acid (mainly created through de novo synthesis from LA) have been associated with inflammation and endothelial activation,6 although researchers are unsure whether higher levels have any impact on atherosclerosis and no large prospective cohort studies have investigated plasma n-6 PUFAs and subclinical measures of atherosclerosis.

This study of participants without apparent cardiovascular disease at baseline examined “whether objectively measured plasma levels of n-3 or n-6 PUFAs were associated with the presence of carotid plaque or occurrence of plaque progression during a median 9.5-year study period, and whether race/ethnicity modified any observed associations.”1


The MESA cohort was gathered from six regions in the United States: Forsyth County, NC; Northern Manhattan and the Bronx, NY; Baltimore City and Baltimore County, MD; St. Paul, MN; Chicago and the village of Maywood, IL; and Los Angeles County, CA. This cohort consisted of men and women of diverse backgrounds between the ages of 45 and 84 years at baseline, who were free from clinical cardiovascular disease. The present investigation included 3327 MESA participants and assessed whether plasma n-3 or n-6 levels were associated with the presence of carotid plaque or occurrence of plaque progression during a median 9.5-year study period.

Fasting samples of blood and plasma were taken throughout the study period and B-mode carotid ultrasonography was conducted at Exam 1 (2000-2002) and Exam 5 (2010-2012) to evaluate carotid artery intima-media thickness and plaque.


Baseline assessments (stratified by presence of plaque) helped to identify a profile of people less likely to have carotid plaque:

  • Lower mean age (p<0.001)
  • More likely to be women (p=0.003)
  • More likely to have never smoked (p<0.001)
  • Lower mean systolic blood pressure (p<0.001)
  • Less likely to have diabetes mellitus (p<0.001)
  • Lower levels of total cholesterol (p<0.001)
  • Greater levels of plasma LA (p<0.001)
  • Greater levels of plasma DHA (p=0.03)

Profiles were also created of subjects who did not experience plaque progression over the course of the study. This group of individuals had the following characteristics:

  • Lower mean age (p<0.001)
  • Lower body mass index (p=0.016)
  • Lower systolic blood pressure (p<0.001)
  • Lower levels of total cholesterol (p=0.04)
  • Fewer current and former smokers (p<0.001)
  • Fewer individuals taking medication(s) for hypertension (p<0.001)
  • Fewer individuals taking medication(s) for lipids (p<0.001)
  • Greater levels of high-density lipoprotein cholesterol (p=0.002)
  • Greater levels of plasma LA (p=0.003)
  • Greater levels of plasma DHA (p=0.005)

Assessment of quartiles of plasma n-3 and n-6 PUFA concentrations found that subjects in the second quartile of n-3 ALA had an 11% greater risk of having plaque than the quartile 1 referent (p=0.02) but there were no noted relationships for the third and fourth quartiles vs. the referent for the presence or absence of plaque. Participants within the fourth DHA quartile had a 9% lower risk of having carotid plaque compared to the referent (p<0.05), and a 12% lower risk of carotid plaque progression than the referent (p=0.002). There were no significant differences between n-6 PUFA quartiles (2nd through 4th vs. referent) for carotid plaque progression.

At baseline, participants in the top quartile of the n-3/n-6 ratio were at a significantly lower risk of for having carotid plaque (p=0.03) and those in the highest quartiles of EPA+DHA and total n-3 PUFAs were at reduced risk for plaque progression (p=0.01 and p=0.02, respectively). There were no significant relationships between total n-6 PUFAs and either the presence or progression of carotid plaque.

Interaction analysis did not detect a modifying effect of race/ethnicity on associations between PUFAs and baseline carotid plaque or plaque progression.


Overall, these results support an association between plasma levels of n-3 PUFAs, particularly DHA, with lower prevalence and risk for progression of carotid plaque.  No consistent positive or inverse associations were found for n-6 PUFAs and carotid plaque presence or progression. The results of this cohort investigation provide evidence for the ongoing recommendation to incorporate n-3 PUFAs into the diet for preventing or delaying atherogenesis. The lack of significant associations for n-6 PUFAs with plaque presence or progression suggest neither pro- nor anti-atherogenic properties for these fatty acids.



  1. Steffen BT, Guan W, Stein JH, et al. Plasma n-3 and n-6 Fatty Acids Are Differentially Related to Carotid Plaque and Its Progression: The Multi-Ethnic Study of Atherosclerosis. Arterioscler Thromb Vasc Biol. 2018;38(3):653-659.
  2. McGill HC, Jr., McMahan CA, Herderick EE, Malcom GT, Tracy RE, Strong JP. Origin of atherosclerosis in childhood and adolescence. Am J Clinical Nutr. 2000;72(5 Suppl):1307S-1315S.
  3. Lopez-Garcia E, Schulze MB, Manson JE, et al. Consumption of (n-3) fatty acids is related to plasma biomarkers of inflammation and endothelial activation in women. J Nutr. 2004;134(7):1806-1811.
  4. Ferrucci L, Cherubini A, Bandinelli S, et al. Relationship of plasma polyunsaturated fatty acids to circulating inflammatory markers. J Clin Endocrinol Metab. 2006;91(2):439-446.
  5. Pischon T, Hankinson SE, Hotamisligil GS, Rifai N, Willett WC, Rimm EB. Habitual dietary intake of n-3 and n-6 fatty acids in relation to inflammatory markers among US men and women. Circulation. 2003;108(2):155-160.
  6. Steffen BT, Steffen LM, Tracy R, et al. Ethnicity, plasma phospholipid fatty acid composition and inflammatory/endothelial activation biomarkers in the Multi-Ethnic Study of Atherosclerosis (MESA). Eur J Clin Nutr. 2012;66(5):600-605.
  7. Calder PC. n-3 polyunsaturated fatty acids, inflammation, and inflammatory diseases. Am J Clin Nutr. 2006;83(6 Suppl):1505S-1519S.
  8. Bemelmans WJ, Lefrandt JD, Feskens EJ, et al. Increased alpha-linolenic acid intake lowers C-reactive protein, but has no effect on markers of atherosclerosis. Eur J Clin Nutr. 2004;58(7):1083-1089.
  9. Del Gobbo LC, Imamura F, Aslibekyan S, et al. omega-3 Polyunsaturated Fatty Acid Biomarkers and Coronary Heart Disease: Pooling Project of 19 Cohort Studies. JAMA Intern Med. 2016;176(8):1155-1166.
  10. Pan A, Chen M, Chowdhury R, et al. alpha-Linolenic acid and risk of cardiovascular disease: a systematic review and meta-analysis. Am J Clin Nutr. 2012;96(6):1262-1273.
  11. Rizos EC, Ntzani EE, Bika E, Kostapanos MS, Elisaf MS. Association between omega-3 fatty acid supplementation and risk of major cardiovascular disease events: a systematic review and meta-analysis. JAMA. 2012;308(10):1024-1033.
  12. Alexander DD, Miller PE, Van Elswyk ME, Kuratko CN, Bylsma LC. A Meta-Analysis of Randomized Controlled Trials and Prospective Cohort Studies of Eicosapentaenoic and Docosahexaenoic Long-Chain Omega-3 Fatty Acids and Coronary Heart Disease Risk. Mayo Clin Proc. 2017;92(1):15-29.
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  14. Simopoulos AP. The importance of the omega-6/omega-3 fatty acid ratio in cardiovascular disease and other chronic diseases. Exp Biol Med (Maywood). 2008;233(6):674-688.
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  17. Farvid MS, Ding M, Pan A, et al. Dietary linoleic acid and risk of coronary heart disease: a systematic review and meta-analysis of prospective cohort studies. Circulation. 2014;130(18):1568-1578.
  18. Harris WS, Poston WC, Haddock CK. Tissue n-3 and n-6 fatty acids and risk for coronary heart disease events. Atherosclerosis. 2007;193(1):1-10.
  19. Wang L, Folsom AR, Eckfeldt JH. Plasma fatty acid composition and incidence of coronary heart disease in middle aged adults: the Atherosclerosis Risk in Communities (ARIC) Study. Nutr Metab Cardiovasc Dis. 2003;13(5):256-266.

24-Hour Urinary Collection Data Support Strong Associations between Sodium and Potassium Excretion and Blood Pressure in the National Health and Nutrition Examination Survey

24-Hour Urinary Collection Data Support Strong Associations between Sodium and Potassium Excretion and Blood Pressure in the National Health and Nutrition Examination Survey

By Kristen N Smith, PhD, RD, LD; Mary R Dicklin, PhD; Kevin C Maki, PhD


It is well established that hypertension is an important modifiable risk factor for cardiovascular disease (CVD), which is a leading cause of morbidity and mortality in the United States.2 Excess dietary sodium has been associated with increased blood pressure.3-5 Conversely, higher intake of potassium has been associated with lower blood pressure.6 The ratio of sodium-to-potassium may have a stronger association with blood pressure than either of the two components alone.7

The majority of studies that have examined the above associations have used self-reported dietary measures to estimate intakes. This includes the National Health and Nutrition Examination Survey (NHANES), which has mainly utilized 24-hour dietary recalls. These tactics are fraught with limitations and may not provide a complete and accurate picture due to inaccuracies in self-led data collection and participant recall. Twenty-four-hour dietary recalls may underestimate average sodium intake by 4 to 34% in comparison with 24-hour urinary excretion.8,9

In an examination of 2014 NHANES data, researchers hypothesized that higher sodium excretion (reflecting higher intake) and a greater sodium-to-potassium ratio would be significantly associated with higher blood pressure and odds of hypertension, whereas greater potassium excretion (reflecting higher intake) would be inversely associated with blood pressure and odds of hypertension.


Cross-sectional data were gathered and analyzed from the 2014 NHANES, a nationally representative survey of noninstitutionalized persons in the United States. One half of NHANES non-pregnant participants (age 20 to 69 years) who were examined in the Mobile Examination Center were included in the 24-hour urine collection study (n=1103). Data gathered from 766 participants with complete blood pressure and 24-hour urine collections were included in the analysis with results described below.


Among the participants included in the analysis, over half were classified as hypertensive (weighted prevalence, 28.2%; 95% confidence interval [CI], 21.6-34.8) or prehypertensive (23.1%; 95% CI, 19.5-26.6). Excretion of sodium, potassium and the sodium-to-potassium ratio did not differ by hypertension status (after adjustment for age, sex, race/ethnicity and body mass index).

Sodium excretion (per 1000 mg/d higher) was directly associated with systolic blood pressure (SBP) (4.58 mm Hg; 95% CI, 2.64-6.51) and diastolic blood pressure (DBP) (2.25 mm Hg; 95% CI, 0.83-3.67). Potassium excretion (per 1000 mg/d higher) was inversely associated with SBP (-3.72 mm Hg; 95% CI -6.01 to -1.42). Molar sodium-to-potassium ratio (per 0.5 U higher) was directly associated with SBP (1.72 mm Hg; 95% CI, 0.76-2.68). In the fully adjusted multivariable logistic model, persons within the highest quartile in comparison with the lowest quartile of sodium excretion had significantly greater odds of having hypertension (odds ratio, 4.22; 95% CI, 1.36-13.15).






Beta-coefficient (95% CI)1

Sodium excretion

4.58* (2.64 to 6.51)

2.25* (0.83 to 3.67)

Potassium excretion

-3.72* (-6.01 to -1.42)

-0.25 (-1.91 to 1.42)

Sodium-to-potassium ratio

1.72* (0.76 to 2.68)

0.30 (-0.53 to 1.12)

1Beta-coefficents for sodium and potassium excretion indicate change in mm Hg of blood pressure associated with 1000 mg/d change in excretion. Beta-coefficients for the ratio represent change in mm Hg blood pressure associated with 0.5 U change in molar ratio. Fully adjusted for age, sex, race/ethnicity plus body mass index, education, history of CVD, diabetes status, chronic kidney disease, smoking status and physical activity. Models examining sodium excretion were simultaneously adjusted for potassium excretion, and vide versa.

*p < 0.01 for beta-coefficient in the regression model.


NHANES’ first ever use of the “gold standard” 24-hour urine collection identified a direct association between sodium excretion and blood pressure among US adults.1 Analyses of these cross-sectional data also demonstrated that the sodium-to-potassium ratio was directly associated with SBP, whereas potassium excretion was inversely associated with SBP. These results align with previous findings from studies examining urinary electrolyte excretion and blood pressure.10-12 These conclusions provide additional support for the 2015-2020 Dietary Guidelines for Americans containing the advice to reduce sodium intake and increase intake of potassium-containing foods compared with the current average American diet.13


  1. Jackson SL, Cogswell ME, Zhao L, et al. Association between urinary sodium and potassium excretion and blood pressure among adults in the United States: National Health and Nutrition Examination Survey, 2014. Circulation. 2018;137(3):237-246.
  2. Benjamin EJ, Blaha MJ, Chiuve SE, et al. Heart disease and stroke statistics-2017 update: A report from the American Heart Association. Circulation. 2017;135(10):e146-e603.
  3. Medicine Io. Sodium and Chloride. Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate. Washington, DC: The National Academies Press 2005.
  4. Cook NR, Cutler JA, Obarzanek E, et al. Long term effects of dietary sodium reduction on cardiovascular disease outcomes: observational follow-up of the trials of hypertension prevention (TOHP). BMJ. 2007;334(7599):885-888.
  5. He FJ, MacGregor GA. A comprehensive review on salt and health and current experience of worldwide salt reduction programmes. J Hum Hypertens. 2009;23(6):363-384.
  6. Aburto NJ, Hanson S, Gutierrez H, Hooper L, Elliott P, Cappuccio FP. Effect of increased potassium intake on cardiovascular risk factors and disease: systematic review and meta-analyses. BMJ. 2013;346:f1378.
  7. Perez V, Chang ET. Sodium-to-potassium ratio and blood pressure, hypertension, and related factors. Adv Nutr. 2014;5(6):712-741.
  8. Freedman LS, Commins JM, Moler JE, et al. Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for potassium and sodium intake. Am J Epidemiol. 2015;181(7):473-487.
  9. Espeland MA, Kumanyika S, Wilson AC, et al. Statistical issues in analyzing 24-hour dietary recall and 24-hour urine collection data for sodium and potassium intakes. Am J Epidemiol. 2001;153(10):996-1006.
  10. Liu L, Ikeda K, Yamori Y. Twenty-four hour urinary sodium and 3-methylhistidine excretion in relation to blood pressure in Chinese: results from the China-Japan cooperative research for the WHO-CARDIAC Study. Hypertens Res. 2000;23(2):151-157.
  11. Hedayati SS, Minhajuddin AT, Ijaz A, et al. Association of urinary sodium/potassium ratio with blood pressure: sex and racial differences. Clin J Am Soc Nephrol. 2012;7(2):315-322.
  12. Mente A, O'Donnell MJ, Rangarajan S, et al. Association of urinary sodium and potassium excretion with blood pressure. N Engl J Med. 2014;371(7):601-611.
  13. U.S. Depart of Health and Human Services and U.S. Department of Agriculture. 2015 - 2020 Dietary Guidelines for Americans. 8th Edition. December 2015. Available at https://health.gov/dietaryguidelines/2015/guidelines.



Summary of Results from a Trial of a Novel Selective PPARɑ Modulator, Pemafibrate, on Lipid and Glucose Metabolism in Patients with Type 2 Diabetes and Hypertriglyceridemia1

Summary of Results from a Trial of a Novel Selective PPARɑ Modulator, Pemafibrate, on Lipid and Glucose Metabolism in Patients with Type 2 Diabetes and Hypertriglyceridemia

By Kristen N Smith, PhD, RD, LD; Mary R Dicklin, PhD; Kevin C Maki, PhD


Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death in persons with type 2 diabetes2 and the incidence of cardiovascular events is elevated in patients with type 2 diabetes compared with those without diabetes.3,4 Abnormalities in lipid metabolism often accompany type 2 diabetes mellitus and are associated with insulin resistance, including:

  • Elevated triglyceride (TG) levels with delayed clearance of TG-rich lipoproteins from the circulation;
  • Reduced high-density lipoprotein cholesterol (HDL-C) levels;
  • An increased proportion of small, dense low-density lipoprotein (LDL) particles.

Several large-scale clinical trials, including the Collaborative Atorvastatin Diabetes Study (CARDS) and a Cholesterol Treatment Trialists’ (CTT) meta-analysis, have shown that effective management of dyslipidemia through LDL cholesterol (LDL-C)-lowering therapy with statins results in reduced cardiovascular risk in patients with diabetes.5,6 Other studies in people with diabetes have also identified risk factors for developing coronary heart disease including the Japan Diabetes Complication Study (JDCS), which noted high LDL-C and TG levels as risk factors, and the UK Prospective Diabetes Study (UKPDS), which showed that high LDL-C and low HDL-C are associated with elevated cardiovascular disease risk.7,8

Studies with fibrates have shown the expected decreases in TG and increases in HDL-C, but have shown inconsistent results regarding reductions in ASCVD risk in patients with type 2 diabetes. A meta-analysis completed by our group9 showed evidence that fibrates and other drugs that primarily lower TG and TG-rich lipoproteins (omega-3 fatty acid concentrates and niacin) reduce ASCVD events in participants with elevated TG, particularly if also accompanied by low HDL-C.

Pemafibrate (K-877) is a novel selective peroxisome proliferator-activated receptor alpha (PPARɑ) modulator approved for the treatment of dyslipidemia.10 Ishibashi et al. performed a dose-finding phase 2 trial of pemafibrate in patients with atherogenic dyslipidemia (elevated TG and low HDL-C) and noted significant reductions in TG and increases in HDL-C with rates of adverse events (AEs) similar to placebo. Because type 2 diabetes and atherogenic dyslipidemia often coexist, many of the patients who receive treatment with pemafibrate (once approved for marketing) are expected to also have type 2 diabetes. This summary reports on the initial 24-week treatment period for a Phase III clinical trial comparing the effects of pemafibrate and placebo in patients with elevated TG and type 2 diabetes. The primary end point of the study was the percentage change in fasting serum TG level from baseline to the end point of 24 weeks. Secondary endpoints included the percentage changes or changes from baseline in fasting and postprandial lipid-related and glycemic parameters. The primary safety end points were the incidence rates of AEs and adverse drug reactions after the study drug usage.


This was a multicenter, placebo-controlled, randomized, double-blind, parallel group study that was completed in 34 medical institutions in Japan from February 20, 2014 through April 30, 2015. Subjects were eligible for the study if they met the following criteria:

  • Men and postmenopausal women age ≥20 years;
  • Type 2 diabetes with glycated hemoglobin (HbA1c) ≥6.2% and TG ≥150 mg/dL (1.7 mmol/L);
  • ≥12 weeks of dietary or exercise guidance before the first screening visit.

This study included participants who were randomly assigned to receive twice daily placebo (n = 57), 0.2 mg/day pemafibrate (n = 54), or 0.4 mg/day pemafibrate (n = 55) for 24 weeks. Pemafibrate is available in 0.1 mg tablets.


Fasting serum TG significantly decreased by ~45% with pemafibrate compared with placebo (p<0.001, see table).



Fasting TG, mg/dL, mean ± standard deviation



Week 24


  284.3 ± 117.6

240.0 ± 92.2

0.2 mg/day pemafibrate

240.3 ± 93.5

129.0 ± 71.5

0.4 mg/day pemafibrate

260.4 ± 95.9

135.8 ± 71.2

Percentage changes in fasting serum TG levels from baseline to 24 weeks were -10.8% (p < 0.01), -44.3% (p < 0.001) and -45.1% (p <0.001) for placebo, 0.2 mg/day and 0.4 mg/day, respectively. The pemafibrate groups also had significantly reduced levels of non-HDL-C, remnant lipoprotein cholesterol, apolipoprotein (Apo) B100, Apo B48 and Apo C3, and significantly increased HDL-C and Apo A1 levels. LDL-C was not significantly affected by treatment with pemafibrate. The 0.2 mg/day pemafibrate group had significant reductions in homeostasis model assessment (HOMA)-insulin resistance scores compared with placebo, but no significant alterations vs. placebo were seen in fasting plasma glucose, fasting insulin, glycoalbumin or HbA1c. Rates of AEs and adverse drug reactions were similar between the two pemafibrate groups and the placebo group.


This is the first report of long-term (24 weeks) efficacy and safety of pemafibrate in subjects with type 2 diabetes and hypertriglyceridemia. In this study, which was conducted in Japan, pemafibrate lowered TG levels by ~45%, which was apparent within the first month of the treatment period and maintained over the entire treatment period. An ASCVD event trial with pemafibrate commenced enrollment in 2017, the Pemafibrate to Reduce Cardiovascular Outcomes by Reducing Triglycerides in Patients with Diabetes (PROMINENT) trial, and is expected to complete in 2022 (https://clinicaltrials.gov/ct2/show/NCT03071692).


  1. Araki E, Yamashita S, Arai H, et al. Effects of pemafibrate, a novel selective PPARalpha modulator, on lipid and glucose metabolism in patients with type 2 diabetes and hypertriglyceridemia: A Randomized, Double-Blind, Placebo-Controlled, Phase 3 Trial. Diabetes Care. 2018;41(3):538-546.
  2. Tancredi M, Rosengren A, Svensson AM, et al. Excess mortality among persons with type 2 diabetes. N Engl J Med. 2015;373(18):1720-1732.
  3. Haffner SM, Lehto S, Ronnemaa T, Pyorala K, Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N Engl J Med. 1998;339(4):229-234.
  4. Mulnier HE, Seaman HE, Raleigh VS, et al. Risk of myocardial infarction in men and women with type 2 diabetes in the UK: a cohort study using the General Practice Research Database. Diabetologia. 2008;51(9):1639-1645.
  5. Colhoun HM, Betteridge DJ, Durrington PN, et al. Primary prevention of cardiovascular disease with atorvastatin in type 2 diabetes in the Collaborative Atorvastatin Diabetes Study (CARDS): multicentre randomised placebo-controlled trial. Lancet. 2004;364(9435):685-696.
  6. Cholesterol Treatment Trialists C, Kearney PM, Blackwell L, et al. Efficacy of cholesterol-lowering therapy in 18,686 people with diabetes in 14 randomised trials of statins: a meta-analysis. Lancet. 2008;371(9607):117-125.
  7. Sone H, Tanaka S, Tanaka S, et al. Serum level of triglycerides is a potent risk factor comparable to LDL cholesterol for coronary heart disease in Japanese patients with type 2 diabetes: subanalysis of the Japan Diabetes Complications Study (JDCS). J Clin Endocrinol Metab. 2011;96(11):3448-3456.
  8. Turner RC, Millns H, Neil HA, et al. Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS: 23). BMJ. 1998;316(7134):823-828.
  9. Maki KC, Guyton JR, Orringer CE, Hamilton-Craig I, Alexander DD, Davidson MH. Triglyceride-lowering therapies reduce cardiovascular disease event risk in subjects with hypertriglyceridemia. J Clin Lipidol. 2016;10(4):905-914.

10.       Ishibashi S, Yamashita S, Arai H, et al. Effects of K-877, a novel selective PPARalpha modulator (SPPARMalpha), in dyslipidaemic patients: A randomized, double blind, active- and placebo-controlled, phase 2 trial. Atherosclerosis. 2016;249:36-43.

female scientist

Substituting a Type-4 Resistant Starch for Available Carbohydrate Reduces Postprandial Glucose, Insulin and Hunger: An Acute, Randomized, Double-Blind, Controlled Study

Substituting a Type-4 Resistant Starch for Available Carbohydrate Reduces Postprandial Glucose, Insulin and Hunger:  An Acute, Randomized, Double-Blind, Controlled Study1

 By Kristen N Smith, PhD, RD, LD; Mary R Dicklin, PhD; Kevin C Maki, PhD


Dietary fiber (including a wide variety of nondigestible carbohydrates) is a noted shortfall nutrient in Western diets, despite the fact that appropriate consumption is associated with a broad range of health benefits.2,3 One of the benefits that has received considerable attention is blunting of postprandial blood glucose control. Researchers have established a benefit between consumption of viscous fibers and blood glucose excursions.4 When certain fibers, such as resistant starch (RS), are used in place of available carbohydrate in foods, less glucose is liberated through digestion, thus lowering the rate and quantity of glucose entering the bloodstream after a meal.5

It is important to note that there are different types of RS receiving varying levels of attention in clinical trials. These differences are outlined in the table below.

Type of RS


Amount of Research

Resistant starch type-2

Granular, native starch

Resistant to digestion

Majority of clinical research is in these 2 areas

Resistant starch type-3

Retrograded starch

Resistant to digestion

Resistant starch type-4 (RS4)

Chemically modified starch

Resists digestion by intestinal enzymes

Fewer clinical trials in this area

Among the types of RS4, phosphate distarch phosphate is the most frequently tested6-8, with fewer studies on hydroxypropyl distarch phosphate9,10 and only one study on acid hydrolyzed and heat treated RS4, to date.11

The primary aim of this study was to characterize the postprandial blood glucose response in healthy adults to a novel RS4 (acid hydrolyzed and heat treated maize-based RS) in a ready-to-eat baked good (scone), compared with the response to consumption of a scone made with a control starch. The secondary aims were to evaluate postprandial insulin response, satiety and gastrointestinal tolerance. It was hypothesized that the replacement of digestible carbohydrate from refined wheat flour with RS4 would reduce postprandial blood glucose.


This was a double-blind, randomized, controlled trial conducted at MB Clinical Research in Boca Raton, Florida, USA.

Main Entry Criteria:

  • Age 18-74 y
  • Men and women
  • Body mass index (BMI) 18.5-29.99 kg/m2
  • General good health
  • Fasting capillary glucose <100 mg/dL

The treatment fiber scone contained VERSAFIBE™ 2470 resistant starch (provided by Ingredion Incorporated, Bridgewater, NJ) as the primary fiber source. VERSAFIBE™ 2470 is a RS4 with 70% dietary fiber and is produced from food grade high-amylose maize starch. Acid hydrolysis and heat treatment both reduce the digestibility of this high-amylose maize starch resulting in increased RS4 and total dietary fiber in the finished product. There are no nonstarch polysaccharides present in VERSAFIBE™ 2470. The nutrition composition of the Fiber Scone and Control Scone are shown in the following table.


Per Serving, As-Eaten

Control Scone



Weight (g)



Calories (kcal)



Fat (g)



Saturated fat (g)



Protein (g)



Total Carbohydrates (g)



Available Carbohydrates (g)



Dietary Fiber (g)*



Sugars (g)



*VERSAFIBE™ 2470 resistant starch provided 16.5 g dietary fiber in the Fiber Scone

The subjects attended 3 study visits, one for screening and two test visits. At the test visits, subjects consumed the Control Scone or Fiber Scone (randomly assigned sequence) with 240 mL water.  Capillary glucose, plasma glucose and plasma insulin were measured pre-consumption and at t = -15, 15, 30, 45, 60, 90, 120 and 180 min ± 2 min, where t = 0 was the start of the study product consumption. Satiety visual analog scale (VAS) ratings were assessed pre-consumption and at 3 min intervals.  Questionnaires were used to assess Gastrointestinal (GI) Tolerability and product palatability at each test visit.


A total of 36 subjects were randomized in the study, and one was withdrawn due to non-compliance. Ultimately, 32 subjects were included in the glucose and insulin analyses and 35 were included in the satiety VAS, GI tolerability and palatability analyses.

Consumption of the Fiber Scone significantly reduced postprandial glucose and insulin incremental areas under the curve (43-45% reduction and 35-40% reduction, respectively, p<0.05 for both) as well as postprandial glucose and insulin maximum concentrations (8-10% and 22% reductions, respectively, p<0.05 for both).  Ratings of hunger and desire to eat were also significantly reduced following consumption of the Fiber Scone vs. the Control Scone during the 180 minutes after intake (p<0.05) and there were no GI side effects with the Fiber Scone compared with Control.


This study shows significant reductions in postprandial glucose and insulin levels associated with the replacement of refined carbohydrate with RS4 in healthy subjects. In addition, ratings of hunger and desire to eat were reduced after consumption of the RS4-containing food product, a first for this specific RS ingredient. Incorporation of a fiber such as RS4 into the diet has potential clinical and practical relevance due to favorable impacts on markers of cardiometabolic health.12,13


  1. Stewart ML, Wilcox ML, Bell M, Buggia MA, Maki KC. Type-4 resistant starch in substitution for available carbohydrate reduces postprandial glycemic response and hunger in acute, randomized, double-blind, controlled study. Nutrients. 2018;10(2).
  2. Dahl WJ, Stewart ML. Position of the Academy of Nutrition and Dietetics: Health implications of dietary fiber. J Acad Nutr Diet. 2015;115:1861-1870.
  3. Stephen AM, Champ MM, Cloran SJ, et al. Dietary fibre in Europe: current state of knowledge on definitions, sources, recommendations, intakes and relationships to health. Nutr Res Rev. 2017;30:149-190.
  4. Tosh SM. Review of human studies investigating the post-prandial blood-glucose lowering ability of oat and barley food products. European J Clin Nutr. 2013;67:310-317.
  5. Robertson MD. Dietary-resistant starch and glucose metabolism. Curr Opin Clin Nutr Metab Care. 2012;15:362-367.
  6. Haub MD, Hubach KL, Al-Tamimi EK, Ornelas S, Seib PA. Different types of resistant starch elicit different glucose reponses in humans. J Nutr Metab. 2010;2010.
  7. Al-Tamimi EK, Seib PA, Snyder BS, Haub MD. Consumption of cross-linked resistant starch (RS4(XL)) on glucose and insulin responses in humans. J Nutr Metab. 2010;2010.
  8. Martinez I, Kim J, Duffy PR, Schlegel VL, Walter J. Resistant starches types 2 and 4 have differential effects on the composition of the fecal microbiota in human subjects. PLoS One. 2010;5:e15046.
  9. Shimotoyodome A, Suzuki J, Kameo Y, Hase T. Dietary supplementation with hydroxypropyl-distarch phosphate from waxy maize starch increases resting energy expenditure by lowering the postprandial glucose-dependent insulinotropic polypeptide response in human subjects. Br J Nutr. 2011;106:96-104.
  10. Gentile CL, Ward E, Holst JJ, et al. Resistant starch and protein intake enhances fat oxidation and feelings of fullness in lean and overweight/obese women. Nutr J. 2015;14:113.
  11. Stewart ML, Zimmer JP. Post-prandial glucose and insulin response to high-fiber muffin top containing resistant starch type 4 in healthy adults: a double-blind, randomized, controlled trial. Nutrition. 2018 (in press).
  12. Maki KC, Pelkman CL, Finocchiaro ET, et al. Resistant starch from high-amylose maize increases insulin sensitivity in overweight and obese men. J Nutr. 2012;142:717-723.
  13. Marlatt KL, White UA, Beyl RA, et al. Role of resistant starch on diabetes risk factors in people with prediabetes: design, conduct, and baseline reuslts of the STARCH trial. Contemp Clin Trials. 2018;65:99-108.
tape measure

Breakfast Skippers Beware: Newly Published Data on Breakfast Patterns Identifies Association with Atherosclerosis, Independent of Cardiovascular Disease Risk Factors

Breakfast Skippers Beware: Newly Published Data on Breakfast Patterns Identifies Association with Atherosclerosis, Independent of Cardiovascular Disease Risk Factors

Insights from the Progression of Early Subclinical Atherosclerosis (PESA) Study

By Kristen N Smith, PhD, RD, LD; Mary R Dicklin, PhD; Kevin C Maki, PhD

 Background: It is well accepted that a person’s lifestyle may impact markers of overall health. Factors associated with lifestyle may be dependent on cultural, social and psychological practices as they fit into a daily routine. Researchers have paid particular attention to the lifestyle habit of breakfast consumption (or non-consumption) and how it may contribute to disease risk.

Whether or not a person consumes breakfast has correlations to such factors as:

  • Measures of satiety,
  • Daily energy intake,
  • Metabolic efficiency of the diet,
  • Appetite regulation.

The regular omission of breakfast has associations with increased cardiovascular health markers such as obesity, diabetes, and unfavorable lipid profiles. Although there have been studies investigating the impacts of breakfast skipping behaviors with heart disease risk, the current study may be the first to research an association between breakfast patterns and subclinical atherosclerosis. The aim of the Progression of Early Subclinical Atherosclerosis (PESA) study1 was to characterize the association between different breakfast patterns and cardiovascular disease (CVD) risk factors; especially focusing on whether the regular omission of breakfast is associated with subclinical atherosclerosis (noted by investigating the presence of atherosclerotic plaques in the carotid arteries, aorta, and iliofemoral arteries or coronary artery calcium in a population with no previous CVD history).

 Methods: The PESA study is an ongoing observational prospective cohort of 4,082 employees of the Bank Santander Headquarters in Madrid, Spain. Male and female volunteers, aged 40 to 54 years old, were included if they met the following criteria:

  • Free of any CVD or chronic kidney disease,
  • No previous transplant,
  • Did not exceed body mass index (BMI) of 40 kg/m2,
  • Did not have any disease that might affect life expectancy and decrease it to <6 years.

Estimates of usual diet were determined through the use of a computerized questionnaire, which was developed and validated in the Estudio de Nutrición y Riesgo Cardiovascular (ENRICA) study of a Spanish population and contains nutritional information on 861 food items including many typically consumed Spanish meals and dishes. Subjects reported the foods consumed in the past 15 days while also noting specific occasions throughout the day (waking up, breakfast, mid-morning, lunch, mid-afternoon, and dinner). To characterize breakfast patterns, the researchers first utilized the quantitative description of breakfast provided by Timlin and Pereira2: “the first meal of the day that breaks the fast after the longest period of sleep, eaten before the start of daily activities (e.g., errands, travel, work), within 2 h of waking, typically no later than 10:00 in the morning, and an energy level between 20 and 35% of total daily energy need.” Additional input was gathered by application of a qualitative definition of breakfast by O’Neill et al. where breakfast is defined as “a food or beverage from at least one food group, and may be consumed at any location. Coffee, water and nonalcoholic beverages are not included in a food group.”3 Mean energy intake of the subjects in the PESA study was 2,314 kcal/day; three major breakfast groups were identified:

  • <5% total energy intake (EI) = skipping breakfast (SBF)
  • 5 to 20% total EI from breakfast = low-energy breakfast (LBF)
  • >20% total EI from breakfast = high-energy breakfast (HBF)

Anthropometric data were collected and CVD risk factors and metabolic syndrome (MetS) were assessed. The European Society of Cardiology CVD risk assessment tool, the Systematic Coronary Risk Evaluation, was used to assess fatal cardiovascular risk. Additionally, researchers noted variables such as age, gender, marital status, highest educational level, smoking status, diet practices and physical activity. Specific ultrasound equipment was utilized to assess atherosclerotic plaque in multiple vascular areas: bilateral carotid, infrarenal abdominal aorta and iliofemoral arteries. Plaques were defined as “focal protrusion into the arterial lumen of thickness >0.5 mm or >50% of the surrounding intima-media thickness or a diffuse thickness >1.5 mm measured between the media-adventitia and intima-lumen interfaces.” Coronary artery calcium (CAC) was also assessed, and states of atherosclerosis were defined as follows:


State of Atherosclerosis Definition
Subclinical atherosclerosis The presence of plaque in the right carotid, left carotid, aorta, right iliofemoral, or left iliofemoral or as the presence of calcium (CAC score > 0) in the coronary arteries
Non-coronary atherosclerosis The presence of plaque in the above areas and excluding CAC
Generalized atherosclerosis Dependent on the number of sites affected with atherosclerosis; 4 to 6 sites affected


Results: Of the 4,052 participants, 2.9%, 69.4% and 27.7% fell into the SBF (breakfast skipping), LBF (low-energy breakfast) and HBF (high-energy breakfast) categories, respectively. Compared with HBF and LBF, the SBF group was made up mostly of men, current smokers, subjects who had reportedly changed their diet in the previous year to lose weight, and subjects who consumed their highest energy intake at lunch. Compared with HBF, the LBF subjects were more likely to be men with lower education level and to be current smokers with higher calorie intakes at lunch.

Regarding diet quality, the subjects in the SBF group were most likely to have higher energy, protein (from animal sources) and dietary cholesterol intakes while also having the lowest fiber and carbohydrate intakes and greatest consumption of alcoholic and sugar-sweetened beverages and red meat.  The LBF group (compared with HBF) had higher overall energy, animal protein and cholesterol intakes and lower intakes of sugar and polysaccharides while also having dietary patterns lower in fruits, vegetables, whole grains and olive oil and higher in refined grains, red meat, fast food and precooked meals (as well as lean meat and seafood). The HBF group had the greatest intakes of dietary fiber, fruits and vegetables, whole grains and high-fat dairy.

The cardiometabolic risk marker profile was less favorable in the LBF and SBF groups, including higher levels of waist circumference, BMI, blood pressure, blood lipids and fasting blood glucose. Participants in the SBF group had a greater likelihood of scoring high on the European Society of Cardiology Systematic Coronary Risk Evaluation risk scale. Probabilities of obesity, abdominal obesity, MetS, low high-density lipoprotein cholesterol, and hypertension were significantly greater for the SBF group compared with HBF.  The prevalence values for atherosclerosis (subclinical, non-coronary and generalized) across all PESA subjects were 62.5%, 60.3% and 13.4%, respectively.

The odds ratios (ORs) for subclinical atherosclerosis were significantly elevated in the SBF group compared with the HBF group:

  • Abdominal aorta - OR 1.79, 95% confidence interval (CI) 1.16 to 2.77,
  • Carotid atherosclerotic plaques - OR 1.76, 95% CI 1.17 to 2.65,
  • Iliofemoral plaques - OR 1.72, 95% CI 1.11 to 2.64,
  • Coronary atherosclerosis – OR 1.55, 95% CI 0.97 to 2.46,
  • Non-coronary and generalized atherosclerosis - OR 2.57, 95% CI 1.54 to 4.31.

The participants in the LBF group had greater risk of carotid or iliofemoral atherosclerotic plaques compared with the HBF group (OR 1.21; 95% CI 1.03 to 1.43 and OR 1.17; 95% CI 1.00 to 1.37, respectively).

Comment: The results from the PESA study indicate that regular skipping of breakfast was associated with 1.55- to 2.57-fold higher odds for subclinical atherosclerosis, even after adjustment for traditional CVD risk factors and diet quality. Breakfast skipping behavior was also linked to an overall unhealthy lifestyle (poor overall diet, higher consumption of alcohol and smoking).  Other researchers have also noted these same associations in that skipping breakfast is often associated with smoking4, greater total energy intake5, and noncompliance with “Healthy Eating” recommendations.6

Results from PESA confirm the association between breakfast skipping and an adverse cardiometabolic risk marker profile and further show that breakfast skipping is independently associated with subclinical measures of atherosclerosis.  However, the degree to which this association might be causal vs. reflective of residual confounding due to greater exposure to CVD risk markers over time is uncertain.

Several studies have demonstrated that insulin sensitivity shows diurnal variation.  For example, Saad et al. reported that mean values for an index of insulin sensitivity produced from postprandial responses to identical meals at breakfast, lunch and dinner were 11.2, 7.9 and 8.1 (units = 10-4 dL/kg/min/mU/mL).7  Thus, insulin sensitivity was ~40% higher in the morning compared with the afternoon or evening.  It is possible that consuming a lower percentage of daily energy during the times of day when insulin sensitivity is highest (consumption of a low-energy breakfast or breakfast skipping) has an adverse impact on the cardiometabolic risk profile, increasing risks for both type 2 diabetes mellitus and atherosclerotic CVD, although prospective trials will be needed to investigate this possibility.8


  1. Uzhova I, Fuster V, Fernandez-Ortiz A, et al. The Importance of Breakfast in Atherosclerosis Disease: Insights From the PESA Study. J Am Coll Cardiol. 2017;70(15):1833-1842.
  2. Timlin MT, Pereira MA. Breakfast frequency and quality in the etiology of adult obesity and chronic diseases. Nutr Rev. 2007;65(6 Pt 1):268-281.
  3. O'Neil CE, Byrd-Bredbenner C, Hayes D, Jana L, Klinger SE, Stephenson-Martin S. The role of breakfast in health: definition and criteria for a quality breakfast. J Acad Nutr Diet. 2014;114(12 Suppl):S8-S26.
  4. Nishiyama M, Muto T, Minakawa T, Shibata T. The combined unhealthy behaviors of breakfast skipping and smoking are associated with the prevalence of diabetes mellitus. Tohoku J Exp Med. 2009;218(4):259-264.
  5. van der Heijden AA, Hu FB, Rimm EB, van Dam RM. A prospective study of breakfast consumption and weight gain among U.S. men. Obesity (Silver Spring, Md). 2007;15(10):2463-2469.
  6. Smith TJ, Dotson LE, Young AJ, et al. Eating patterns and leisure-time exercise among active duty military personnel: comparison to the Healthy People objectives. J Acad Nutr Diet. 2013;113(7):907-919.
  7. Saad A, Dalla Man C, et al. Diurnal pattern to insulin secretion and insulin action in healthy individuals. Diabetes. 2012;61(11):2691-2700.
  8. Maki KC, Phillips-Eakley AK, Smith KN. The effects of breakfast consumption and composition on metabolic wellness with a focus on carbohydrate metabolism. Adv Nutr. 2016;7 (Suppl 6):613S-621S.


Photo by Brooke Lark