The body mass index (BMI) is the metric currently in use for defining anthropometric height/weight characteristics in adults and for classifying (categorizing) them into groups. The common ...interpretation is that it represents an index of an individual’s fatness. It also is widely used as a risk factor for the development of or the prevalence of several health issues. In addition, it is widely used in determining public health policies.The BMI has been useful in population-based studies by virtue of its wide acceptance in defining specific categories of body mass as a health issue. However, it is increasingly clear that BMI is a rather poor indicator of percent of body fat. Importantly, the BMI also does not capture information on the mass of fat in different body sites. The latter is related not only to untoward health issues but to social issues as well. Lastly, current evidence indicates there is a wide range of BMIs over which mortality risk is modest, and this is age related. All of these issues are discussed in this brief review.
Effect of a High-Protein, Low-Carbohydrate Diet on Blood Glucose Control in People With Type 2 Diabetes
Mary C. Gannon 1 2 3 and
Frank Q. Nuttall 1 3
1 Metabolic Research Laboratory and the Section ...of Endocrinology, Metabolism and Nutrition, Department of Veterans Affairs Medical
Center, Minneapolis, Minnesota
2 Department of Food Science and Nutrition, University of Minnesota, Minneapolis, Minnesota
3 Department of Medicine, University of Minnesota, Minneapolis, Minnesota
Address correspondence and reprint requests to Mary C. Gannon, PhD, Metabolic Research Laboratory (111G), VA Medical Center,
One Veterans Drive, Minneapolis, MN 55417. E-mail: ganno004{at}umn.edu
Abstract
There has been interest in the effect of various types and amounts of dietary carbohydrates and proteins on blood glucose.
On the basis of our previous data, we designed a high-protein/low-carbohydrate, weight-maintaining, nonketogenic diet. Its
effect on glucose control in people with untreated type 2 diabetes was determined. We refer to this as a low-biologically-available-glucose
(LoBAG) diet. Eight men were studied using a randomized 5-week crossover design with a 5-week washout period. The carbohydrate:protein:fat
ratio of the control diet was 55:15:30. The test diet ratio was 20:30:50. Plasma and urinary β-hydroxybutyrate were similar
on both diets. The mean 24-h integrated serum glucose at the end of the control and LoBAG diets was 198 and 126 mg/dl, respectively.
The percentage of glycohemoglobin was 9.8 ± 0.5 and 7.6 ± 0.3, respectively. It was still decreasing at the end of the LoBAG
diet. Thus, the final calculated glycohemoglobin was estimated to be ∼6.3–5.4%. Serum insulin was decreased, and plasma glucagon
was increased. Serum cholesterol was unchanged. Thus, a LoBAG diet ingested for 5 weeks dramatically reduced the circulating
glucose concentration in people with untreated type 2 diabetes. Potentially, this could be a patient-empowering way to ameliorate
hyperglycemia without pharmacological intervention. The long-term effects of such a diet remain to be determined.
LoBAG, low biologically available glucose
NEFA, nonesterified fatty acid
SDTU, special diagnostic and treatment unit
Footnotes
Accepted June 2, 2004.
Received February 5, 2004.
DIABETES
We have been interested in the metabolic effects of ingested fuels, both in normal subjects and in people with type 2 diabetes. Recently, we have become interested in the regulation of glucose ...production and the regulation of gluconeogenesis in particular. We are not aware of a recent comprehensive review of these topics. Therefore, we have reviewed the currently available literature.
The pertinent papers obtained from a Medline search of the words gluconeogenesis, glycogenolysis, hepatic glucose output, as well as papers from our personal files, form the basis of this review.
In order to analyse the data, it also was necessary to review the relevant methodology used in determining gluconeogenesis. Pathway diagrams have been included with this review in order to illustrate and highlight key aspects of the methodologies.
Current data support the hypothesis that the rate of glucose appearance changes but the rate of gluconeogenesis remains remarkably stable in widely varying metabolic conditions in people without diabetes. In people with diabetes, whether gluconeogenesis remains unchanged is at present uncertain. Available data are very limited. The mechanism by which gluconeogenesis remains relatively constant, even in the setting of excess substrates, is not known. One interesting speculation is that gluconeogenic substrates substitute for each other depending on availability. Thus, the overall rate is either unaffected or only modestly changed. This requires further confirmation. Published in 2008 by John Wiley & Sons, Ltd.
Abstract Objective Hyperglycemia improves when patients with type 2 diabetes are placed on a weight-loss diet. Improvement typically occurs soon after diet implementation. This rapid response could ...result from low fuel supply (calories), lower carbohydrate content of the weight-loss diet, and/or weight loss per se. To differentiate these effects, glucose, insulin, C-peptide and glucagon were determined during the last 24 h of a 3-day period without food (severe calorie restriction) and a calorie-sufficient, carbohydrate-free diet. Research design Seven subjects with untreated type 2 diabetes were studied. A randomized-crossover design with a 4-week washout period between arms was used. Methods Results from both the calorie-sufficient, carbohydrate-free diet and the 3-day fast were compared with the initial standard diet consisting of 55% carbohydrate, 15% protein and 30% fat. Results The overnight fasting glucose concentration decreased from 196 (standard diet) to 160 (carbohydrate-free diet) to 127 mg/dl (fasting). The 24 h glucose and insulin area responses decreased by 35% and 48% on day 3 of the carbohydrate-free diet, and by 49% and 69% after fasting. Overnight basal insulin and glucagon remained unchanged. Conclusions Short-term fasting dramatically lowered overnight fasting and 24 h integrated glucose concentrations. Carbohydrate restriction per se could account for 71% of the reduction. Insulin could not entirely explain the glucose responses. In the absence of carbohydrate, the net insulin response was 28% of the standard diet. Glucagon did not contribute to the metabolic adaptations observed.
Background: In single-meal studies, dietary protein does not result in an increase in glucose concentrations in persons with or without type 2 diabetes, even though the resulting amino acids can be ...used for gluconeogenesis. Objective: The metabolic effects of a high-protein diet were compared with those of the prototypical healthy (control) diet, which is currently recommended by several scientific organizations. Design: The metabolic effects of both diets, consumed for 5 wk each (separated by a 2-5-wk washout period), were studied in 12 subjects with untreated type 2 diabetes. The ratio of protein to carbohydrate to fat was 30:40:30 in the high-protein diet and 15:55:30 in the control diet. The subjects remained weight-stable during the study. Results: With the fasting glucose concentration used as a baseline from which to determine the area under the curve, the high-protein diet resulted in a 40% decrease in the mean 24-h integrated glucose area response. Glycated hemoglobin decreased 0.8% and 0.3% after 5 wk of the high-protein and control diets, respectively; the difference was significant (P < 0.05). The rate of change over time was also significantly greater after the high-protein diet than after the control diet (P < 0.001). Fasting triacylglycerol was significantly lower after the high-protein diet than after the control diet. Insulin, C-peptide, and free fatty acid concentrations were not significantly different after the 2 diets. Conclusion: A high-protein diet lowers blood glucose postprandially in persons with type 2 diabetes and improves overall glucose control. However, longer-term studies are necessary to determine the total magnitude of response, possible adverse effects, and the long-term acceptability of the diet.
Purpose
A large number of medications have been implicated in the genesis of gynecomastia. However, gynecomastia is common in men, asymptomatic, increases with age, and is considered to be due to an ...increased estradiol/testosterone ratio. This complicates the interpretation of medication-related gynecomastia. Therefore, we have reviewed the literature in order to assess the data relating gynecomastia onset with utilization of specific medications.
Methods
The literature was searched in PubMed and the Ovid/Medline databases from the 1946 to January 2015 with the search terminology of “gynecomastia, drugs/medications.” A few other articles were found and included.
Results
One hundred ten publications were reviewed. Sixty-three were single case reports. There were 24 population-based studies of which 8 were HIV-infected patients treated with antiretroviral agents. Among the case reports, 49 were for individual medications, and 2 were reports of antineoplastic or antiretroviral drug regimens. In the great majority, mastodynia with or without breast enlargement was present and referred to as gynecomastia. Generally, hormonal profiles could not explain the breast enlargement. The pain/tenderness and breast enlargement resolved spontaneously over time.
Conclusion
Many different medications have been associated with the presence of “gynecomastia.” Generally, it presents as a syndrome characterized by a single painful/tender breast (mastodynia) associated with breast enlargement and is transient. We suggest that these cases be referred to as an acute gynecomastia syndrome. This syndrome also occurs independent of medication use. Thus, in an individual patient, whether it is medication induced often remains uncertain. The pathogenesis remains unknown.
Diets with increased protein and reduced carbohydrates have been shown to improve body composition, lipid and lipoprotein profiles, and glycemic regulations associated with treatment of obesity and ...weight loss. Derived from these outcomes, high-protein, low-carbohydrate diets are also being examined for treatment of heart disease, metabolic syndrome, and type 2 diabetes. High-protein, low-carbohydrate diets have been found to have positive effects on reducing risk factors for heart disease, including reducing serum triacylglycerol, increasing HDL cholesterol, increasing LDL particle size, and reducing blood pressure. These diets appear particularly attractive for use with individuals exhibiting the atherogenic dyslipidemia of metabolic syndrome. High-protein, low-carbohydrate diets have also been investigated for treatment of type 2 diabetes with positive effects on glycemic regulation, including reducing fasting blood glucose, postprandial glucose and insulin responses, and the percentage of glycated hemoglobin. Specific effects of increasing protein compared with reducing carbohydrates have not been extensively investigated. Additional research is needed to determine specific levels of protein, carbohydrate, and fat for optimum health of individuals who differ in age, physical activity, and metabolic phenotypes.
Objective
We have been interested in determining the effects of dietary changes on fuel metabolism and regulation in men with type 2 diabetes mellitus (T2DM). In this study, the changes in 24‐hr ...circulating lipid profiles were determined when the major fuel source was endogenous versus exogenous fat.
Methods
Seven males with T2DM were randomized in a crossover design with a 4‐week washout period. A standard mixed (control) diet (30%fat:15%protein:55%carbohydrate) was provided initially. Subsequently, a 72‐hr (3‐day) fast, or a high fat (85%), 15% protein, essentially carbohydrate‐free (CHO‐free) diet was provided for 72 hr. Triacylglycerol (TAG), non‐esterified fatty acids (NEFA), β‐hydroxybutyrate (bHB), and insulin‐like growth factor‐binding protein‐1 (IGFBP‐1) profiles were determined during the last 24 hr of intervention, as well as during the control diet.
Results
Regardless of the amount of dietary fat (30% vs 85%) and differences in 24‐hr profiles, TAG, NEFA, and bHB all returned to the previous basal concentrations within 24 hr. TAGs and NEFAs changed only modestly with fasting; bHB was elevated and increasing. The IGFBP‐1 profile was essentially unchanged with either diet but increased with fasting.
Conclusion
A CHO‐free diet resulted in a large increase in TAG and NEFA versus the control diet; however, both were cleared by the following morning. A negative NEFA profile occurred with the control diet. Thus, mechanisms are present to restore lipid concentrations to their original AM concentrations daily. Fasting resulted in stable concentrations, except for a continuing increase in bHB. Glucose and insulin, common fuel regulators, could not explain the results.
The 24‐hr response profiles for TAG, NEFA, bHB, and IGFBP‐1 were obtained when ingesting a mixed control diet before, and during the last 48–72 hr when ingesting a CHO‐free diet or fasting in male subjects with untreated type 2 diabetes. Data indicate that subjects are still able to absorb, process, utilize, and if necessary, store large amounts of ingested fats adequately, as well as adjust adequately to short‐term starvation.
Background:
Current mathematical models of postprandial glucose metabolism in people with normal and impaired glucose tolerance rely on insulin measurements and are therefore not applicable in ...clinical practice. This research aims to develop a model that only requires glucose data for parameter estimation while also providing useful information on insulin sensitivity, insulin dynamics and the meal-related glucose appearance (GA).
Methods:
The proposed glucose-only model (GOM) is based on the oral minimal model (OMM) of glucose dynamics and substitutes the insulin dynamics with a novel function dependant on glucose levels and GA. A Bayesian method and glucose data from 22 subjects with normal glucose tolerance are utilised for parameter estimation. To validate the results of the GOM, a comparison to the results of the OMM, obtained by using glucose and insulin data from the same subjects is carried out.
Results:
The proposed GOM describes the glucose dynamics with comparable precision to the OMM with an RMSE of 5.1 ± 2.3 mg/dL and 5.3 ± 2.4 mg/dL, respectively and contains a parameter that is significantly correlated to the insulin sensitivity estimated by the OMM (r = 0.7) Furthermore, the dynamic properties of the time profiles of GA and insulin dynamics inferred by the GOM show high similarity to the corresponding results of the OMM.
Conclusions:
The proposed GOM can be used to extract useful physiological information on glucose metabolism in subjects with normal glucose tolerance. The model can be further developed for clinical applications to patients with impaired glucose tolerance under the use of continuous glucose monitoring data.
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