Questions and Answers: Dr. David LudwigDecember 29, 2015 Written by JP [Font too small?]
This is a follow up to my recent review of Always Hungry?, Dr. David Ludwig’s powerful, new diet and wellness book. In today’s blog, Dr. Ludwig is kind enough to clarify and expound upon some key points he originally made in the book. Specifically, I asked questions on the subjects I thought you would be interested in knowing more about. But, if I missed something, please let me know in the comment section below. I’ll do my best to get the answers. Lastly, before delving into the Q&A, I’d like to point out the above photo. Dr. Ludwig is seated next to his talented wife, Dawn Ludwig, a gourmet, natural health chef and creator of the delicious recipes contained in the book.
Q: In the Always Hungry Solution (AHS) you emphasize the pivotal role of insulin sensitivity in establishing and maintaining a healthy weight. What did you find in the AHS pilot study in terms of changes in fasting blood sugar and HbA1c? How about measures of inflammation, like C-reactive protein?
A: We didn’t conduct blood testing in the pilot for logistical reasons. However, we and many other research teams have looked at the effects of reducing total carbohydrate and/or glycemic index on these parameters. For example, in our JAMA 2012 feeding study, both the very low and moderate carbohydrate groups showed substantial benefits compared to the high carbohydrate group for liver and systemic insulin sensitivity and other components of the metabolic syndrome.
CRP was a bit discrepant, in that the very low carbohydrate group showed a tendency to be higher, and this may have related to the high saturated fat content. Clearly, saturated fat isn’t the public health enemy it has been made out to be for most of the last half century. But, too much of certain kinds of saturated fat for some people can be inflammatory – there’s clear mechanistic support for this possibility in animal studies and short term human studies. In any event, we don’t know whether the suggestion of an increase in inflammation on the very low carbohydrate diet is transient, and much more research is needed into this issue. With its moderate (but not low) saturated fat intake, the AHS aims to find a middle path – though the program is designed for individualization. For example, individuals with more severe insulin resistance may do best staying on Phase 1 of the program, which has a low carbohydrate level of 25%.
Q: Regarding blood sugar, do you think the use of a glucometer is a valuable adjunct to longer term blood work and the AHS worksheets?
A: Blood sugar monitoring is certainly important for people with diabetes (type 1 or 2), to determine proper medication dosing and avoid postprandial hyperglycemia. For everyone else, a general sense of carbohydrate tolerance can be useful to help establish parameters for total and processed carbohydrate intake.
The biohackers among us may like to collect information on blood glucose throughout the day. But one day won’t provide a complete picture, so this can be a laborious process. For the rest of us, a HgA1c test will provide a good guidepost. Those with levels approaching 6% may do best with relatively less carbohydrate – at least initially. We recently published in the journal Obesity evidence that the tolerance for carbohydrate can be improved – and the activity of insulin-producing pancreatic beta-cell in effect reset – after just one month of carbohydrate restriction.
Q: What’s your perspective on the recent popularity of ancestral type eating plans, such as those that approximate the Paleolithic diet?
A: The Paleo diet has become popular among a health-conscious segment of the population, and there’s much to recommend this approach. First and foremost, this diet eliminates all fast acting carbohydrates, which humans never ate until recently in our evolution (with the exception of honey, which was a favorite when it could be found).
One unresolved issue is what level of animal versus plant protein is optimal – both for ourselves and our environment. The best epidemiology rather consistently suggests an advantage for vegetarian proteins, not only for weight control, but also prevention of cardiovascular disease and diabetes. But there are unresolved issues. Could there be down sides to consuming large amounts of tofu and beans, dominant sources of plant protein? Are the adverse effects of animal protein related to industrial vs grass fed animal rearing?
Of course, with 7 billion humans, we can’t all go back to Paleolithic lifestyles, even if it were the healthiest option. There aren’t enough wild animals nor range land to feed so many people that way. (Though it warrants mention that in some environments, grazing animals are less disruptive to the ecology than farming.) Ultimately, we need more and better research, so that we can make the best decisions to balance our individual health and that of the environment upon which we all depend.
Q: In my opinion, low carbohydrate diets have yet to receive the respect they deserve. After reading your book and acknowledgments, it seems that you value much of the ketogenic and low carb research. Is this an accurate assessment?
A: Humans have the evolutionary special ability to make ketones – allowing the brain to be fully nourished when carbohydrate intake is low and protein intake isn’t high. For individuals such as those with type 2 diabetes, a ketogenic diet may be the quickest and most effective way to reverse metabolic dysfunction. In fact, one study I’d love to do (with adequate funding) would be to compare bariatric surgery with a ketogenic diet in the treatment of new onset type 2 diabetes. The ketone beta-hydroxy butyrate may have additional benefits for cancer prevention and slowing down the aging process – perhaps explaining why fasting seems to be so protective.
But a ketogenic diet is challenging to maintain, especially in our modern food environment. To be done right, this diet requires frequent blood ketone monitoring. A metabolically bad place to be is with low ketones and inadequate dietary carbohydrate to supply glucose for the brain. Fortunately, for many people, such severe carbohydrate restriction isn’t necessary to reduce insulin resistance, chronic inflammation and body weight.
Q: In your book, you recommend supplementing with vitamin D3. Is there a dosage you typically suggest? Are you an advocate of 25-hydroxy vitamin D testing for use as a personalized guide? If so, what range of vitamin D is a good benchmark for cardiometabolic health and weight?
A: Dosage of vitamin D varies greatly among people, in substantial part due to genetically determined differences in metabolism. Doses of up to 8000 IU per day appear to be safe, and don’t lead to excessively high serum levels. (A day in the sun can lead to the endogenous production of twice that amount). Generally speaking, I would recommend periodic monitoring, not only for those taking high doses of vitamin D, but also for those not taking any. The serum normal range is generally taken as 30 to 80 ng/ml, with much debate regarding the optimal range. Pending the results of several major clinical trials, I generally aim for levels of 40 to 60 – similar to those of several studied hunter-gatherers populations.
People living in Northern latitudes and not getting regular sun exposure (especially during the Winter) typically need 2,000 to 5,000 IU per day to reach this range. In addition, I recommend the mammalian form of vitamin D (D3, cholecalciferol) rather than plant form (D2, ergocalciferol) because of its greater bioavailability and the possibility of broader biological activity. Vegetarian versions of D3 are now available.
Q: In Always Hungry?, you touch upon the topic of gut microbiota and suggest a few ways to increase the population of beneficial bacteria – dietary fiber, kefir/yogurt consumption, probiotic supplementation, etc. Do you think microbiota play a significant role in the realm of weight gain and loss?
A: The role of gut microbes in weight loss and chronic disease prevention is among the most interesting and controversial in the field today. In the laboratory, it’s clear that obesity can be “transplanted” by transferring feces from a heavy animal to a lean one. In humans, the microbiome has been associated with just about every chronic disease imaginable, from asthma to Alzheimers.
The three key dietary determinants are prebiotics, probiotics and polyphenols. Prebiotics are fiber and other poorly digestible substances in food upon which beneficial microbes feed. Probiotics are the beneficial microbes themselves, which can be consumed as a supplement or from naturally fermented foods. And polyphenols are plant substances that serve to control the growth of potential harmful bacteria. The AHS emphasizes these “Three Ps” to cultivate a healthy microbiome.
Selecting the right probiotic supplement can be an uncertain and expensive undertaking. Look for a supplement that is refrigerated (to maintain potency) and contains a minimum of 10 billion CFU (colony forming units) per pill. For specific indications, such as leaky gut syndrome, selection of tailored formulations can be guided by stool microbiome analysis. But for general purposes, aim to add naturally fermented foods – real sauerkraut, kimchi, kefir, natural yogurt – to your regular diet.
Q: You take a strict stance when it comes to artificial sweeteners. Just don’t use them. However, you are a bit more lenient when it comes to stevia. Please explain why. Do you feel the same about monk fruit (Siraitia grosvenorii)?
A: Artificial sweeteners don’t have calories, yet they interact with our sweet taste receptors hundreds to thousands of times more powerfully than sugar itself. Of particular concern, sweet taste receptors are located not only in the mouth, but also throughout the digestive track and even on the surface of fat cells. Could these artificial chemicals have adverse metabolic effects, despite their lack of calories? Some concerning research suggests so. Stevia and a few other natural extracts have some track record of safe use, but we don’t have long-term data on high dose consumption.
Our research (AJCN 2013) and the experience of pilot test participants suggest that cravings and even preference for sweetness changes very rapidly on the AHS. With the luscious, high fat foods on the meal plan, the nucleus accumbens (ground zero for craving and addiction in the brain) seem to turn off, and we lose interest in the sweetened stuff.
Low Glycemic & Low Carb Diets Increase Energy (Calorie) Expenditure
Source: JAMA. 2012 Jun 27;307(24):2627-34. (link)
Q: You’ve co-authored many studies on the health implications of a low glycemic load diet in comparison to a higher glycemic load diet. The results, in both of your experiments and others, have been somewhat inconsistent. Why do you think this is the case?
A: The vast majority of clinical trials studying any dietary factor have been of moderate to extremely low quality – with small participant number, short duration, few quality control, limited compliance and use of proxy outcome measures. Studies of glycemic index are no exception in this regard. Moreover, individuals may vary in their response to any dietary factor, based on background diet, what other foods get added or subtracted, genetic susceptibility and current metabolic health. That said, among the highest quality existing research – that is, using a feeding study design to assure compliance and following individuals for an adequate period of time – reduction of glycemic index/load has consistently shown benefits (including in our studies and the Diogenes multicenter study from Europe).
Ultimately, the field greatly needs better quality research and this requires better funding. Drug trials often have budgets reaching tens to hundreds of millions of dollars. The budget for most diet trials is 1% of that. It costs at least $1 billion to bring just one drug from the laboratory to market. It’s time we adequately invest in nutrition research, to decrease our dependence on drugs to manage chronic disease.
Q: Have you looked into the possibility that the food-insulin index may also influence overweight?
A: The insulin index is interesting, and has some utility in the laboratory. But insulin response to food doesn’t take into account a key variable: glucagon. Some proteins can stimulate as much insulin secretion as carbohydrates, but those macronutrients have different effects on metabolism. That’s because protein also elicits a vigorous glucagon response, which counterbalances the anabolic action of insulin. In contrast, high glycemic index carbohydrates suppresses glucagon, leading to a metabolic double whammy. For this reason, the blood sugar response to food is the most important measure of postprandial metabolic consequences, with the insulin response providing some additional insights.
Q: The AHS integrates mindfulness as part of a holistic approach to fine tune hunger and establish a “lower (body weight) set point”. Are there any other mind-body practices that are particularly useful as an adjunct – cognitive bias modification, hypnosis, Emotional Freedom Technique/thought field therapy, etc.?
A: In addition to diet, lifestyle factors can also influence the behavior of fat cells. Too much stress, too little sleep and not enough physical activity can promote insulin resistance and chronic inflammation. The AHS focuses on these three areas, to synergize with diet. Mindfulness has special benefit – including dietary choice, stress reduction, and in other areas. However, there are many new and ancient methods from which to choose, and we encourage readers to find practices that are effective and enjoyable for them.
Pre-orders for Always Hungry? are now being accepted here. If you order prior to January 5th, the official release date, you’ll receive three free gifts to help get you started.
Note: Please check out the “Comments & Updates” section of this blog – at the bottom of the page. You can find the latest research about this topic there!
Tags: Inflammation, Insulin, Ketogenic
Posted in Diet and Weight Loss, Interviews, Nutrition
December 29th, 2015 at 4:43 pm
Am J Clin Nutr. 2015 Jun;101(6):1216-24.
Changes in intake of protein foods, carbohydrate amount and quality, and long-term weight change: results from 3 prospective cohorts.
BACKGROUND: Dietary guidelines recommend interchanging protein foods (e.g., chicken for red meat), but they may be exchanged for carbohydrate-rich foods varying in quality [glycemic load (GL)]. Whether such exchanges occur and how they influence long-term weight gain are not established.
OBJECTIVE: Our objective was to determine how changes in intake of protein foods, GL, and their interrelationship influence long-term weight gain.
DESIGN: We investigated the association between 4-y changes in consumption of protein foods, GL, and their interaction with 4-y weight change over a 16- to 24-y follow-up, adjusted for other lifestyle changes (smoking, physical activity, television watching, sleep duration), body mass index, and all dietary factors simultaneously in 3 prospective US cohorts (Nurses’ Health Study, Nurses’ Health Study II, and Health Professionals Follow-Up Study) comprising 120,784 men and women free of chronic disease or obesity at baseline.
RESULTS: Protein foods were not interchanged with each other (intercorrelations typically < |0.05|) but with carbohydrate (negative correlation as low as -0.39). Protein foods had different relations with long-term weight gain, with positive associations for meats, chicken with skin, and regular cheese (per increased serving/d, 0.13-1.17 kg; P = 0.02 to P < 0.001); no association for milk, legumes, peanuts, or eggs (P > 0.40 for each); and relative weight loss for yogurt, peanut butter, walnuts, other nuts, chicken without skin, low-fat cheese, and seafood (-0.14 to -0.71 kg; P = 0.01 to P < 0.001). Increases in GL were independently associated with a 0.42-kg greater weight gain per 50-unit increase (P < 0.001). Significant interactions (P-interaction < 0.05) between changes in protein foods and GL were identified; for example, increased cheese intake was associated with weight gain when GL increased, with weight stability when GL did not change, and with weight loss when exchanged for GL (i.e., decrease in GL). CONCLUSION: Protein foods were commonly interchanged with carbohydrate, and changes in protein foods and GL interacted to influence long-term weight gain. Be well! JP
December 29th, 2015 at 4:45 pm
Mol Genet Metab. 2015 Jan;114(1):73-9.
Effects of sodium benzoate, a widely used food preservative, on glucose homeostasis and metabolic profiles in humans.
Sodium benzoate is a widely used preservative found in many foods and soft drinks. It is metabolized within mitochondria to produce hippurate, which is then cleared by the kidneys. We previously reported that ingestion of sodium benzoate at the generally regarded as safe (GRAS) dose leads to a robust excursion in the plasma hippurate level . Since previous reports demonstrated adverse effects of benzoate and hippurate on glucose homeostasis in cells and in animal models, we hypothesized that benzoate might represent a widespread and underappreciated diabetogenic dietary exposure in humans. Here, we evaluated whether acute exposure to GRAS levels of sodium benzoate alters insulin and glucose homeostasis through a randomized, controlled, cross-over study of 14 overweight subjects. Serial blood samples were collected following an oral glucose challenge, in the presence or absence of sodium benzoate. Outcome measurements included glucose, insulin, glucagon, as well as temporal mass spectrometry-based metabolic profiles. We did not find a statistically significant effect of an acute oral exposure to sodium benzoate on glucose homeostasis. Of the 146 metabolites targeted, four changed significantly in response to benzoate, including the expected rise in benzoate and hippurate. In addition, anthranilic acid, a tryptophan metabolite, exhibited a robust rise, while acetylglycine dropped. Although our study shows that GRAS doses of benzoate do not have an acute, adverse effect on glucose homeostasis, future studies will be necessary to explore the metabolic impact of chronic benzoate exposure.
December 29th, 2015 at 4:47 pm
PLoS Med. 2013 Oct;10(10):e1001521.
Pregnancy weight gain and childhood body weight: a within-family comparison.
BACKGROUND: Excessive pregnancy weight gain is associated with obesity in the offspring, but this relationship may be confounded by genetic and other shared influences. We aimed to examine the association of pregnancy weight gain with body mass index (BMI) in the offspring, using a within-family design to minimize confounding.
METHODS AND FINDINGS: In this population-based cohort study, we matched records of all live births in Arkansas with state-mandated data on childhood BMI collected in public schools (from August 18, 2003 to June 2, 2011). The cohort included 42,133 women who had more than one singleton pregnancy and their 91,045 offspring. We examined how differences in weight gain that occurred during two or more pregnancies for each woman predicted her children’s BMI and odds ratio (OR) of being overweight or obese (BMI≥85th percentile) at a mean age of 11.9 years, using a within-family design. For every additional kg of pregnancy weight gain, childhood BMI increased by 0.0220 (95% CI 0.0134-0.0306, p<0.0001) and the OR of overweight/obesity increased by 1.007 (CI 1.003-1.012, p = 0.0008). Variations in pregnancy weight gain accounted for a 0.43 kg/m(2) difference in childhood BMI. After adjustment for birth weight, the association of pregnancy weight gain with childhood BMI was attenuated but remained statistically significant (0.0143 kg/m(2) per kg of pregnancy weight gain, CI 0.0057-0.0229, p = 0.0007).
CONCLUSIONS: High pregnancy weight gain is associated with increased body weight of the offspring in childhood, and this effect is only partially mediated through higher birth weight. Translation of these findings to public health obesity prevention requires additional study.
December 30th, 2015 at 12:28 am
Note: This study highlights the importance of dietary fiber in the context of a weight loss diet …
J Clin Biochem Nutr. 2015 Nov;57(3):217-22.
Effect of an isocaloric diet containing fiber-enriched flour on
anthropometric and biochemical parameters in healthy non-obese
We studied the effect of soluble fiber-enriched products on
anthropometric and biochemical variables in 30 healthy non-obese,
non-diabetic subjects. This was a randomized, controlled crossover,
single-blind, dietary intervention study performed for 8 weeks.
Subjects received an isocaloric diet with fiber-enriched products for
the first 4 weeks and with regular flour products for the following 4
weeks, or vice versa. Weight, height, measures of fat distribution
(waist, hip circumference), glucose, insulin and triglycerides were
measured at baseline, after 4 and 8 weeks of intervention. BMI and
insulin sensitivity indices were calculated. Weight and BMI decreased
in the first period of isocaloric diet in both groups, regardless of
the type of flour consumed (weight p<0.01, p<0.001 respectively; BMI p
= 0.01, p<0.001 respectively). At the end of the 8 weeks, weight and
BMI further decreased in the group consuming the fiber-enriched diet
(p<0.01). Insulin resistance, estimated with the Homeostasis Model
Assessment index and the Lipid Accumulation Product index, improved in
all subjects after the fiber-enriched flour diet (p = 0.03, p = 0.02,
respectively). In conclusion, an isocaloric diet supplemented with
fiber-enriched products may improve measures of fatness and insulin
sensitivity in healthy non-obese non-diabetic subjects. We might
hypothesize a similar effect also in subjects with metabolic
January 25th, 2016 at 9:56 am
Nutr Metab Cardiovasc Dis. 2015 Dec 12.
The effects of a low-carbohydrate diet on appetite: A randomized controlled trial.
BACKGROUND AND AIMS: The relationship between dietary macronutrient composition and appetite is controversial. We examined the effects of a year-long low-carbohydrate diet compared to a low-fat diet on appetite-related hormones and self-reported change in appetite.
METHODS AND RESULTS: A total of 148 adults with a body mass index 30-45 kg/m2, who were free of diabetes, cardiovascular disease and chronic kidney disease at baseline were randomly assigned to either a low-carbohydrate diet (carbohydrate [excluding dietary fiber]<40 g/day; N = 75) or a low-fat diet (<30% energy from fat, <7% from saturated fat; N = 73). Participants in both groups attended individual and group dietary counseling sessions where they were provided the same behavioral curriculum and advised to maintain baseline levels of physical activity. Appetite and appetite-related hormones were measured at 0, 3, 6 and 12 months of intervention. At 12 months, mean changes (95% CI) in peptide YY were -34.8 pg/mL (-41.0 to -28.6) and in the low-carbohydrate group and -44.2 pg/mL (-50.4 to -38.0) in the low-fat group (net change: 9.54 pg/mL [0.6 to 18.2]; p = 0.036). Approximately 99% of dietary effects on peptide YY are explained by differences in dietary macronutrient content. There was no difference in change in ghrelin or self-reported change in appetite between the groups.
CONCLUSIONS: A low-fat diet reduced peptide YY more than a low-carbohydrate diet. These findings suggest that satiety may be better preserved on a low-carbohydrate diet, as compared to a low fat diet.
May 30th, 2016 at 4:08 pm
Nutrients. 2016 May 23;8(5).
Cardiovascular, Metabolic Effects and Dietary Composition of Ad-Libitum Paleolithic vs. Australian Guide to Healthy Eating Diets: A 4-Week Randomised Trial.
(1) BACKGROUND: The Paleolithic diet is popular in Australia, however, limited literature surrounds the dietary pattern. Our primary aim was to compare the Paleolithic diet with the Australian Guide to Healthy Eating (AGHE) in terms of anthropometric, metabolic and cardiovascular risk factors, with a secondary aim to examine the macro and micronutrient composition of both dietary patterns;
(2) METHODS: 39 healthy women (mean ± SD age 47 ± 13 years, BMI 27 ± 4 kg/m²) were randomised to either the Paleolithic (n = 22) or AGHE diet (n = 17) for four weeks. Three-day weighed food records, body composition and biochemistry data were collected pre and post intervention;
(3) RESULTS: Significantly greater weight loss occurred in the Paleolithic group (-1.99 kg, 95% CI -2.9, -1.0), p < 0.001). There were no differences in cardiovascular and metabolic markers between groups. The Paleolithic group had lower intakes of carbohydrate (-14.63% of energy (E), 95% CI -19.5, -9.7), sodium (-1055 mg/day, 95% CI -1593, -518), calcium (-292 mg/day 95% CI -486.0, -99.0) and iodine (-47.9 μg/day, 95% CI -79.2, -16.5) and higher intakes of fat (9.39% of E, 95% CI 3.7, 15.1) and β-carotene (6777 μg/day 95% CI 2144, 11410) (all p < 0.01); (4) CONCLUSIONS: The Paleolithic diet induced greater changes in body composition over the short-term intervention, however, larger studies are recommended to assess the impact of the Paleolithic vs. AGHE diets on metabolic and cardiovascular risk factors in healthy populations. Be well! JP
July 21st, 2016 at 2:05 pm
Aging (Albany NY). 2016 Jul 13.
Long-term moderate calorie restriction inhibits inflammation without impairing cell-mediated immunity: a randomized controlled trial in non-obese humans.
Calorie restriction (CR) inhibits inflammation and slows aging in many animal species, but in rodents housed in pathogen-free facilities, CR impairs immunity against certain pathogens. However, little is known about the effects of long-term moderate CR on immune function in humans. In this multi-center, randomized clinical trial to determine CR’s effect on inflammation and cell-mediated immunity, 218 healthy non-obese adults (20-50 y), were assigned 25% CR (n=143) or an ad-libitum (AL) diet (n=75), and outcomes tested at baseline, 12, and 24 months of CR. CR induced a 10.4% weight loss over the 2-y period. Relative to AL group, CR reduced circulating inflammatory markers, including total WBC and lymphocyte counts, ICAM-1 and leptin. Serum CRP and TNF-α concentrations were about 40% and 50% lower in CR group, respectively. CR had no effect on the delayed-type hypersensitivity skin response or antibody response to vaccines, nor did it cause difference in clinically significant infections. In conclusion, long-term moderate CR without malnutrition induces a significant and persistent inhibition of inflammation without impairing key in vivo indicators of cell-mediated immunity. Given the established role of these pro-inflammatory molecules in the pathogenesis of multiple chronic diseases, these CR-induced adaptations suggest a shift toward a healthy phenotype.
November 7th, 2016 at 8:22 pm
Health Psychol. 2016 Nov 3.
Mindful Eating Reduces Impulsive Food Choice in Adolescents and Adults.
Objective: The present study tested the extent to which age and obesity predicted impulsive choices for food and monetary outcomes and tested how a brief mindful-eating training would alter delay discounting for food and money choices compared with control groups. Method: First, 172 adolescents (Mage = 13.13 years) and 176 (Mage = 23.33 years) adults completed the Food Choice Questionnaire (FCQ) and Monetary Choice Questionnaire (MCQ) as measures of food and money delay discounting, respectively. Then, participants returned to the lab and were randomly assigned to complete a brief mindful-eating training, watch a DVD on nutrition, or serve as a control. Participants completed the FCQ and MCQ again as a postmanipulation measure. Results: Participants with high percent body fat (PBF) were more impulsive for food than those with low PBF. Adults with high PBF were also more impulsive for money compared with adults with low PBF; no PBF-related differences were found for adolescents. Participants in the mindful-eating group exhibited more self-controlled choices for food, but not for money. The control conditions did not exhibit changes. Conclusion: The study suggests that individuals with high PBF make more impulsive food choices relative to those with low PBF, which could increase the risk of obesity over time. It also is the first to demonstrate shifts in choice patterns for food and money using a brief mindful-eating training with adolescents. Mindful eating is a beneficial strategy to reduce impulsive food choice, at least temporarily, that may impede weight gain.
December 24th, 2016 at 2:43 pm
Food Funct. 2016 Dec 21.
Effects of weight loss using supplementation with Lactobacillus strains on body fat and medium-chain acylcarnitines in overweight individuals.
Our previous study showed that supplementation with a combination of Lactobacillus curvatus (L. curvatus) HY7601 and Lactobacillus plantarum (L. plantarum) KY1032 reduced the body weight, body fat percentage, body fat mass and L1 subcutaneous fat area in overweight subjects. We aimed to evaluate whether the changes in adiposity after supplementation with Lactobacillus strains were associated with metabolic intermediates. A randomized, double-blind, placebo-controlled study was conducted on 66 non-diabetic and overweight individuals. Over a 12-week period, the probiotic group consumed 2 g of probiotic powder, whereas the placebo group consumed the same product without the probiotics. To investigate metabolic alterations, we performed plasma metabolomics using ultra-performance liquid chromatography and mass spectrometry (UPLC-LTQ/Orbitrap MS). Probiotic supplementation significantly increased the levels of octenoylcarnitine (C8:1), tetradecenoylcarnitine (C14:1), decanoylcarnitine (C10) and dodecenoylcarnitine (C12:1) compared with the levels from placebo supplementation. In the probiotic group, the changes in the body weight, body fat percentage, body fat mass and L1 subcutaneous fat area were negatively associated with changes in the levels of C8:1, C14:1, C10 and C12:1 acylcarnitines. In overweight individuals, probiotic-induced weight loss and adiposity reduction from the probiotic supplementation were associated with an increase in medium-chain acylcarnitines.
February 16th, 2017 at 12:30 am
J Med Internet Res. 2017 Feb 13;19(2):e36.
An Online Intervention Comparing a Very Low-Carbohydrate Ketogenic Diet and Lifestyle Recommendations Versus a Plate Method Diet in Overweight Individuals With Type 2 Diabetes: A Randomized Controlled Trial.
BACKGROUND: Type 2 diabetes is a prevalent, chronic disease for which diet is an integral aspect of treatment. In our previous trial, we found that recommendations to follow a very low-carbohydrate ketogenic diet and to change lifestyle factors (physical activity, sleep, positive affect, mindfulness) helped overweight people with type 2 diabetes or prediabetes improve glycemic control and lose weight. This was an in-person intervention, which could be a barrier for people without the time, flexibility, transportation, social support, and/or financial resources to attend.
OBJECTIVE: The aim was to determine whether an online intervention based on our previous recommendations (an ad libitum very low-carbohydrate ketogenic diet with lifestyle factors; “intervention”) or an online diet program based on the American Diabetes Associations’ “Create Your Plate” diet (“control”) would improve glycemic control and other health outcomes among overweight individuals with type 2 diabetes.
METHODS: In this pilot feasibility study, we randomized overweight adults (body mass index ≥25) with type 2 diabetes (glycated hemoglobin [HbA1c] 6.5%-9.0%) to a 32-week online intervention based on our previous recommendations (n=12) or an online diet program based around a plate method diet (n=13) to assess the impact of each intervention on glycemic control and other health outcomes. Primary and secondary outcomes were analyzed by mixed-effects linear regression to compare outcomes by group.
RESULTS: At 32 weeks, participants in the intervention group reduced their HbA1c levels more (estimated marginal mean [EMM] -0.8%, 95% CI -1.1% to -0.6%) than participants in the control group (EMM -0.3%, 95% CI -0.6% to 0.0%; P=.002). More than half of the participants in the intervention group (6/11, 55%) lowered their HbA1c to less than 6.5% versus 0% (0/8) in the control group (P=.02). Participants in the intervention group lost more weight (EMM -12.7 kg, 95% CI -16.1 to -9.2 kg) than participants in the control group (EMM -3.0 kg, 95% CI -7.3 to 1.3 kg; P<.001). A greater percentage of participants lost at least 5% of their body weight in the intervention (10/11, 90%) versus the control group (2/8, 29%; P=.01). Participants in the intervention group lowered their triglyceride levels (EMM -60.1 mg/dL, 95% CI -91.3 to -28.9 mg/dL) more than participants in the control group (EMM -6.2 mg/dL, 95% CI -46.0 to 33.6 mg/dL; P=.01). Dropout was 8% (1/12) and 46% (6/13) for the intervention and control groups, respectively (P=.07). CONCLUSIONS: Individuals with type 2 diabetes improved their glycemic control and lost more weight after being randomized to a very low-carbohydrate ketogenic diet and lifestyle online program rather than a conventional, low-fat diabetes diet online program. Thus, the online delivery of these very low-carbohydrate ketogenic diet and lifestyle recommendations may allow them to have a wider reach in the successful self-management of type 2 diabetes. Be well! JP
May 3rd, 2017 at 12:49 pm
Nutrients 2017, 9(5), 452
Polyphenol Levels Are Inversely Correlated with Body Weight and Obesity in an Elderly Population after 5 Years of Follow Up (The Randomised PREDIMED Study)
Overweight and obesity have been steadily increasing in recent years and currently represent a serious threat to public health. Few human studies have investigated the relationship between polyphenol intake and body weight. Our aim was to assess the relationship between urinary polyphenol levels and body weight. A cross-sectional study was performed with 573 participants from the PREDIMED (Prevención con Dieta Mediterránea) trial (ISRCTN35739639). Total polyphenol levels were measured by a reliable biomarker, total urinary polyphenol excretion (TPE), determined by the Folin-Ciocalteu method in urine samples. Participants were categorized into five groups according to their TPE at the fifth year. Multiple linear regression models were used to assess the relationships between TPE and obesity parameters; body weight (BW), body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR). After a five years follow up, significant inverse correlations were observed between TPE at the 5th year and BW (β = −1.004; 95% CI: −1.634 to −0.375, p = 0.002), BMI (β = −0.320; 95% CI: −0.541 to −0.098, p = 0.005), WC (β = −0.742; 95% CI: −1.326 to −0.158, p = 0.013), and WHtR (β = −0.408; 95% CI: −0.788 to −0.028, p = 0.036) after adjustments for potential confounders. To conclude, a greater polyphenol intake may thus contribute to reducing body weight in elderly people at high cardiovascular risk.
June 12th, 2017 at 11:51 pm
Obes Facts. 2017 Jun 10;10(3):238-251.
Effect of a High-Protein Diet versus Standard-Protein Diet on Weight Loss and Biomarkers of Metabolic Syndrome: A Randomized Clinical Trial.
BACKGROUND: Some studies have shown that protein-enriched diets can lead to greater weight loss and improvements in biomarkers of metabolic syndrome (MeS) than standard protein diets. Therefore, the aim of this study was to determine the effect of increased protein intake on weight loss in Mexican adults with MeS.
METHODS: Randomized controlled trial in 118 adults aged 47.4 ± 11.5 years and meeting the established criteria for MeS were randomized to prescribed hypocaloric diets (500 kcal less than resting metabolic rate) providing either 0.8 g/kg body weight (standard protein diet (SPD)) or 1.34 g/kg body weight (higher protein diet (HPD)) for 6 months. Body weight, waist circumference, percent body fat by bioimpedance analysis, fasting blood glucose, fasting insulin, hemoglobin A1c, total cholesterol, high-density lipoprotein (HDL) cholesterol, very-low-density lipoprotein (VLDL) cholesterol, triglycerides, C-reactive protein, creatinine, blood urea nitrogen, alanine aminotransferase, aspartate aminotransferase, and gamma-glutamyl transferase were measured at baseline, 3 months and at 6 months.
RESULTS: There were 105 subjects (51 for SPD and 54 for HPD) who completed the trial. Overall weight loss was 5.1 ± 3.6 kg in the SPD group compared to 7.0 ± 3.7 kg in the in HPD group. Both groups lost a significant percent of centimeters of waist circumference (SPD -6.5 ± 2.6 cm and HPD -8.8 ± 2.6 cm). There was no statistical difference Except for the varying weight losses the two groups did not show any further differences overall. However in the subgroup judged to be adherent more than 75% of the time with the prescribed diets, there was a significant difference in mean weight loss (SPD -5.8% vs. HPD -9.5%) after adjusting for baseline BMI. Both groups demonstrated significant decreases in waist circumference, glucose, insulin, triglycerides, and VLDL cholesterol, but there were no differences between the groups. There were no changes in blood tests for liver or renal function.
CONCLUSIONS: There were no significant differences in weight loss and biomarkers of MeS when the overall group was examined, but the participants with more adherence rate in the HPD group lost significantly more weight than adherent participants in the SPD group.