28Mar

A Warning to 40 Year Olds

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The release of the updated National Diabetes Fact Sheet in January 2011 — the previous one dates back to 2007 — underscores the need for Americans to pay more attention to their health, especially for those aged from 40 to 64, for the reasons given below.

The Fact Sheet statistics, summarized in publications of the American Diabetes Association, provide a truly alarming outline of the growing rate of diagnosed and undiagnosed diabetes and its related condition, now given the medical term of Prediabetes.

Diabetes is a serious disease that can occur in people of any age, from birth to old age. There are three main forms of the disease, referred to as Type-1 Diabetes that occurs most often in children and young adults, Type-2 Diabetes that occurs primarily in older people and is by far the major diabetic condition comprising about 90% of all diabetes cases. There is also another type called Gestational Diabetes, a mostly temporary condition that can develop in a small percentage of women during pregnancy.

From other information sources relating to the 2011 Diabetes Fact Sheet, I came across some significant details regarding age and prevalence. There were 3 groups defined by ages 20 to 44 years, 45 to 64 years, and people of age 65 and older.

Most diabetes occurs in the oldest group
Currently, in existing cases of diabetes, the incidence of diabetes increases with age. The smallest number of diabetic people are included in the 20 to 44 age group. About 4 times as many people are in the 45 to 64 age group and in the 65 years and older age group, there are most by a factor of twice as many as the younger 45 to 64 age group.

Estimated number of new cases
However, the statistics seem to indicate that things are changing. Here are the figures for the estimated number of new cases diagnosed for a more recent period for those same ages, note the numbers for group 2:

Group1: Age 20 to 44 – new cases of diabetes were 465,000
Group 2: Age 45 to 64 – new cases of diabetes were 1,052,000
Group 3: Age 65 and older – new cases of diabetes were 390,000

Conclusion and a warning
Diabetes starts a little earlier and gradually develops over time until it may be finally diagnosed by a doctor, sometimes without warning from any significant identifiable symptoms, although there are some when you know them.

The warning: Therefore, if you are over 40 years of age, overweight, and follow a lifestyle of little physical activity, take warning, see a doctor who can requisition a simple blood test that will show whether you are in the high risk Group 2, if not, there is still time to prevent it, but unfortunately, once diagnosed, there is no cure.

25Mar

Type II Diabetes and EFAs

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How the right fats and oils can protect you from this insidious disease.

What is now called lifestyle or adult onset diabetes is a condition where ones body loses its sensitivity to glucose, and therefore becomes insulin resistant.

This means that cells do not respond properly to insulin when it’s present, because the cells have become less functional.

This happens due to the continued, and long term consumption of too many refined carbohydrates, which release their glucose too quickly into the blood stream, raising blood glucose levels too high, too quickly.

Stress, with the accompanying release of adrenalin, which leads to insulin release, may also have a role to play in the development of this disease.

Type I diabetes, is different, and is a disorder where there is not enough insulin produced, due to faulty functioning within the pancreas, which is responsible for producing insulin.

Unfortunately, excess glucose, due either to the inability of insulin to do its job, or a lack of insulin, in getting the glucose into the cells, both lead to increased free radical damage, which will cause further damage to cells and cause you to age faster.

The lining of your arteries, the endothelial cells, are also damaged by excess glucose, so the entire circulatory system will become dysfunctional over time.

In diabetes, particularly type I diabetes, there is an impairment of the conversion of dietary Essential Fatty Acids (EFA’s) to HUFA’s (highly unsaturated fatty acids) such as EPA, DHA, AA (arachidonic acid) and DGLA (dihomogammalinolenic acid). If these derivatives aren’t produced, there are many vital functions that are unable to occur or are impaired in fundamental ways.

There is also an inability to incorporate these HUFA’s into cell membranes, likely linked to an enzyme dysfunction.

Damaged fats, such as trans fats and saturated fats, also stop insulin from working properly, which means that it is unable to get the glucose out of your blood stream and into your cells quickly enough.

Consuming the right kinds of fats and oils can therefore facilitate insulin activity, so knowing what these special fats are, is therefore important. They are called essential because you body cannot manufacture them – they have to consumed in your diet. If you don’t eat them you will be deficient, and it is estimated that 95% of people are deficient in them, for various reasons.

Depression puts you at greater risk of getting diabetes, and suffering from diabetes puts one at a significantly greater risk of getting depression, with figures indicating that depression is twice as common among diabetics than among people who don’t have diabetes.

Having both of these conditions worsens the course of both. So the situation can become a vicious cycle. Furthermore, depression is a risk factor for Cardio Vascular Disease (CVD) too. And, having Diabetes also puts you at a much greater risk of developing Alzheimer’s.

Many researchers believe that the underlying mechanism that links all these disease states may very well be a deficiency in EFA’s, coupled with an inability to convert them into the various derivatives required for optimal cell and membrane health.

However, as medical practitioners continue to look at diseases as separate and distinct, they are unable to piece the puzzle together and come up with the whole picture.

Whatever they may uncover as time goes by, it is accepted that Essential Fatty Acids have an enormously important role to play in overall health, so supplementing with the right blend will improve your health on many levels.

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18Mar

Diet of Adolescents With and Without Diabetes: Part 2

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There have been drastic changes over the last 3 decades with regard to the dietary recommendations for people with diabetes. Before 1994, nutrition recommendations were set forth for all people with diabetes with little regard to the individual’s lifestyle. After 1994 and consistent with the 2002 American Diabetes Association (ADA) evidence-based guidelines, the emphasis shifted from a strict focus on dietary components to a focus on maintaining target blood glucose levels and a lipid profile and blood pressure that reduce the risk of chronic disease. The current ADA nutrition recommendations for children and adolescents with type 1 diabetes share these goals and also focus on adequate nutrient intake for growth and development. These recommendations are based on the requirements for nondiabetic children and adolescents that are collected in the Dietary Reference Intakes, which update and expand the recommended dietary allowances (RDAs).

Only a few studies have examined the diets of children with type 1 diabetes, and even fewer have compared those diets with children without diabetes. In terms of energy intake, two studies of children with type 1 diabetes found that energy intake was lower than recommended; one study found that children met the RDA, and a fourth study found that male subjects met the RDA but female subjects had energy levels below the RDA. Two studies compared the energy intake of children with diabetes with that of matched control subjects. One study found that the intake of children with diabetes fell below that of control subjects who met the RDA, and the other study, based solely on girls, found no difference between children with diabetes and control subjects in energy intake, with both groups reporting lower intake than predicted by energy expenditure.

Studies have also examined the components of dietary intake. Carbohydrates are an important consideration in the diets of children with type 1 diabetes, as they are the principal source of energy but require appropriate amounts of insulin to be utilized by the body. Four studies found that children met carbohydrate requirements, and one study found that children had a lower carbohydrate intake than recommended. In the two studies that included a comparison group, children with diabetes had a lower carbohydrate intake than age- and sex-matched control subjects.

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15Mar

Diet of Adolescents With and Without Diabetes: Part 1

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Abstract

OBJECTIVE —To compare the dietary intake of adolescents with type 1 diabetes with that of adolescents without diabetes matched on age, sex, and year in school and to compare the diets of both groups with recommendations.

RESEARCH DESIGN AND METHODS —Participants were 132 adolescents with type 1 diabetes, recruited from Children’s Hospital of Pittsburgh, and 131 adolescents without diabetes ranging in age from 10.70 to 14.21 years. Dietary intake was assessed with three 24-h recall interviews with each participant and one parent. Percentage of calories from protein, carbohydrates, and total fat; amount of each type of fat; and amount of cholesterol, fiber, and sugar were calculated as averages across 3 days.

RESULTS —Adolescents with diabetes took in less total energy than recommended. The percentage of calories from carbohydrates and protein were within recommendations for adolescents with and without diabetes, but adolescents with diabetes exceeded the recommended fat intake. The diet of adolescents with diabetes consisted of a greater percentage of fat and protein and a smaller percentage of carbohydrates relative to adolescents without diabetes. Adolescents without diabetes consumed more sugar, while adolescents with diabetes took in more of all components of fat than adolescents without diabetes. Male subjects with diabetes had an especially high intake of saturated fat.

CONCLUSIONS —Adolescents with type 1 diabetes consume fewer calories from carbohydrates but more calories from fat than adolescents without diabetes and exceed the recommended levels of fat intake. These findings are of concern given the risk that type 1 diabetes poses for cardiovascular disease.

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14Mar

A Clinical Screening Tool Identifies Autoimmune Diabetes in Adults: Part 7

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CONCLUSIONS

Our findings suggest that assessing multiple clinical features of presentation enables adults with diabetes to be triaged into two groups: lower risk for LADA (LADA clinical risk score ≤1) and higher-risk for LADA (LADA clinical risk score ≥2). The benefits of this screening tool approach for LADA are several. First, it assists in identification and management of patients with LADA. Physicians dealing with a patient who has a higher risk for LADA and who has suboptimal glycemic control should have an increased level of suspicion that the lack of control may be due to insulin deficiency secondary to autoimmune β-cell pathologic changes. With such a patient, it would be logical to perform islet antibody testing to exclude autoimmune diabetes. Our experience is that suboptimal glycemia in such patients is frequently prolonged because it is not attributed to autoimmune diabetes and insulin deficiency. Second, this simple clinical screening tool is practical and cost-effective. LADA can be excluded in a majority of adults with diabetes, e.g., approximately two-thirds (84 of 120) in the prospective study, on the basis of a clinical risk score ≤1. Finally, this screening tool could be used to identify subjects with LADA for inclusion in intervention trials. LADA populations are attractive candidates for autoimmune diabetes intervention trials because they have slowly progressive loss of β-cell function and therefore potentially a wider therapeutic window than in classic type 1 diabetes.

We have pragmatically adopted the five-point LADA clinical risk score over the multivariate scoring method to determine which patients should be tested for GADAs because it is simple to use and has better specificity in the prospective study. The use of the tool in clinical practice will depend on the reliability of the patient’s history, which can be influenced by language and culture, inaccurate reporting of acute symptoms, and lack of awareness of the family medical history. Diabetes in relatives of patients with LADA may also be misclassified, i.e., relatives with LADA may be diagnosed as having type 2 diabetes. Misclassification of diabetes in relatives could only be excluded by testing for islet antibodies. The ability of the LADA clinical risk score to predict LADA in the prospective study, a homogeneous source of diabetic patients, confirms the utility of the clinical screening tool. The applicability of our findings to LADA cohorts from other nations and ethnicities will be important to establish. Finally, testing for other islet antibodies in patients with high-risk LADA clinical risk scores ≥2 could potentially enhance our prediction of autoimmune diabetes, as some of these patients may be GADA− but IA-2A+ and/or IAA+.

In summary, a majority of patients with LADA have at least two of five distinguishing clinical features (age of onset <50 years, acute symptoms before diagnosis, BMI <25 kg/m2, personal history of autoimmune disease, or family history of autoimmune disease) at diagnosis of diabetes. The presence of at least two of these clinical features (LADA clinical risk score ≥2) in adults with diabetes justifies GADA testing. This clinical screening tool should increase the identification of autoimmune diabetes in adults and hopefully improve clinical management of their disease.

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11Mar

A Clinical Screening Tool Identifies Autoimmune Diabetes in Adults: Part 6

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CONCLUSIONS

A retrospective study of clinical parameters at diagnosis in adult-onset diabetes revealed that a majority of subjects with LADA had at least two of five distinguishing clinical features (age of onset <50 years, acute symptoms, BMI <25 kg/m2, personal history of autoimmune disease, or family history of autoimmune disease) compared with a minority of type 2 diabetic subjects. In a prospective validation study, the presence of at least two distinguishing clinical features (LADA clinical risk score ≥2) at diagnosis had 90% sensitivity and 71% specificity for detecting LADA. Furthermore, the presence of less than two distinguishing clinical features (LADA clinical risk score ≤1) was a highly reliable method for excluding LADA (negative predictive value 99%). This clinical screening method is superior to the current popular clinical practice of only screening patients with a BMI <25 kg/m2 for GADAs. Using this normal BMI cutoff as the sole criterion in the prospective study would result in a 30% sensitivity, because a majority of subjects with LADA are overweight or obese.

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This is the first report of a clinical screening tool to distinguish LADA from type 2 diabetes in adults presenting with diabetes. We carefully dissected clinical features at presentation of diabetes in adults, given that previous reports of clinical features suggested that there is no one consistent distinguishing clinical feature that discriminates LADA from type 2 diabetes. An earlier age of onset in LADA compared with type 2 diabetes was documented in a large study but not in other smaller studies. BMI was lower in LADA compared with type 2 diabetes in the UKPDS cohort as well as in several other studies, but this difference was not seen in smaller studies. Presentation with acute symptoms was investigated in one study, which showed that they were more frequent in subjects with LADA than in those with type 2 diabetes. Addressing family history of diabetes, another study showed no difference in either type 1 diabetes or type 2 diabetes in subjects with LADA compared with type 2 diabetic subjects. It was interesting that a family history of type 2 diabetes did not necessarily signify that an individual had type 2 diabetes, given that a majority (57%) of our subjects with LADA had a family history of type 2 diabetes with an overall frequency similar to that of the type 2 diabetic subjects (55%). There have been no reports on the frequency or family history of DR3- and/or DR4-related autoimmune disease in LADA. Thus, what seems clear from previous studies is that no one clinical feature reliably discriminates LADA from type 2 diabetes.

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10Mar

A Clinical Screening Tool Identifies Autoimmune Diabetes in Adults: Part 5

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RESULTS

In the retrospective study, subjects with LADA were significantly younger than type 2 diabetic subjects (median age 46.2 vs. 60.8 years, P < 0.0001) with a majority (64%) having diabetes diagnosed before the age of 50. The median BMI was lower in subjects with LADA compared with type 2 diabetic subjects, but a majority of both subjects with LADA and type 2 diabetes were in the overweight or obese category (BMI ≥25.0 kg/m2). Acute symptoms (polydipsia and/or polyuria and/or weight loss) were present in a majority of subjects with LADA, being significantly more frequent than in type 2 diabetic subjects (67 vs. 28%, P < 0.0001). A family history of type 1 diabetes was more common in subjects with LADA, whereas a family history of type 2 diabetes was similar in subjects with LADA and type 2 diabetes. A family or personal history of DR3- and/or DR4-related autoimmune diseases was more common in LADA. The most common associated autoimmune disease in patients with LADA was thyroid autoimmune disease and in relatives was type 1 diabetes.

On the basis of these findings, five distinguishing clinical features were significantly more frequent in subjects with LADA than in subjects with type 2 diabetes at diagnosis. These were 1) age of diabetes onset <50 years, 2) acute symptoms of polydipsia and/or polyuria and/or unintentional weight loss before diagnosis, 3) BMI <25 kg/m2, 4) a personal history of DR3- and/or DR4-related autoimmune disease, and 5) a family history of DR3- and/or DR4-related autoimmune disease. A majority (75%) of subjects with LADA and a minority (24%) of type 2 diabetic subjects had at least two distinguishing clinical features (LADA clinical risk score ≥2).

A multivariate analysis confirmed that age of diabetes onset <50 years (OR 1.85, P < 0.0001), acute symptoms (1.34, P < 0.0001), BMI <25 kg/m2 (1.29, P < 0.003), and a personal history of autoimmune disease (1.14, P = 0.0143) were independently associated with a diagnosis of LADA. In this form of analysis, family history of autoimmune disease was not independently associated with LADA. A multivariate LADA clinical risk score was determined based on the OR coefficients from the logistic regression model. The formula for calculating the multivariate LADA clinical score was [1.85 (if age of onset <50 years) + 1.29 (if BMI <25 kg/m2) + 1.37 (for the presence of acute symptoms) + 1.14 (for the presence of a personal history of autoimmune disease)]. The multivariate LADA clinical risk score was compared with the original five-point LADA clinical risk score using a ROC plot. The performance of the clinical risk scores was similar (five-point LADA clinical risk score AUC = 0.81 vs. multivariate LADA clinical risk score AUC = 0.84). The optimal cutoff point for the five-point LADA clinical risk score was ≥2 (sensitivity of 75% and specificity of 77%), and for the multivariate LADA the clinical risk score was ≥1.37 (sensitivity of 76% and specificity of 77%).

In the prospective study, a majority (86 of 130) of subjects had none or one distinguishing clinical feature. The presence of two or more distinguishing clinical features (LADA clinical score risk ≥2) had a 90% sensitivity and 71% specificity for detecting LADA. A LADA clinical risk score ≥2 identified 9 of 10 subjects with LADA and a LADA clinical risk score of ≤1 prospectively identified 86 of 120 GADA− type 2 diabetic subjects. Also, a LADA clinical risk score ≤1 was highly reliable for excluding LADA, with 86 of 87 patients who had a LADA clinical score of ≤1 being GADA− (negative predictive value 99%). The multivariate LADA clinical risk score (cutoff ≥1.37) had a similar sensitivity of 90% but lower specificity of 56% for detecting LADA.

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09Mar

A Clinical Screening Tool Identifies Autoimmune Diabetes in Adults: Part 4

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Clinical assessment

All subjects were interviewed by the same endocrinologist (S.F.) to determine the age at diabetes onset, presence of acute symptoms before diagnosis (polydipsia, polyuria, and unintentional loss of weight), weight and height at diagnosis, family history of diabetes, family or personal history of any HLA DR3/DQ2- and/or DR4/DQ8-associated autoimmune disease, i.e., autoimmune thyroid disease, celiac disease, Addison’s disease, vitiligo, rheumatoid arthritis, pernicious anemia, and autoimmune hepatitis. Details of the specific interview questions are provided in the appendix. Metabolic markers such as ketonuria, blood glucose level, and HbA1c (A1C) at diagnosis were not studied, as they were not routinely documented in these subjects.

Statistics

Differences in age and BMI were analyzed with an unpaired t test. Differences in age at diagnosis according to decade category, BMI according to weight category, acute symptoms, personal and family history of autoimmune disease, and family history of diabetes were analyzed with Fisher’s exact tests. Statistical analyses were performed with GraphPad PRISM version 3.0 software.

The ability of a “LADA clinical risk score” to predict LADA was analyzed by a relative operating characteristic (ROC) plot using two different methods. The first method calculated a LADA clinical risk score based on the total number of “distinguishing” clinical features present in each subject. A distinguishing clinical feature was defined as a feature that was significantly more frequent in LADA compared with type 2 diabetes in the retrospective study. One point was scored for the presence of each distinguishing clinical feature, with a LADA clinical risk score of 5 being the maximum. In the second method, a LADA clinical risk score was calculated on the basis of a multivariate analysis of the distinguishing clinical features. Each clinical feature independently associated with LADA was weighted according to its odds ratio (OR) coefficient derived from a logistic regression model. The ability of the two clinical risk scores to predict LADA was assessed by calculating the area under the curve (AUC). Also, cutoff points with optimal sensitivity and specificity for both clinical scoring methods were determined to ascertain their ability to predict LADA in the prospective study.

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07Mar

A Clinical Screening Tool Identifies Autoimmune Diabetes in Adults: Part 3

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RESEARCH DESIGN AND METHODS

Retrospective study

Patients with LADA (n = 102) and type 2 diabetes (n = 111) were recruited from metropolitan Melbourne by referral from diabetes educators in community centers and treating physicians and through the Royal Melbourne Hospital diabetes clinics. A majority (97%) of the subjects were Caucasian. All patients (aged 30–75 years) had diabetes according to World Health Organization criteria (14). Patients with LADA were distinguished from type 1 diabetic patients because they had no requirement for insulin at diagnosis and for a minimum of 6 months after diagnosis. Subjects with LADA were distinguished from type 2 diabetic patients because they were serum GADA+, whereas type 2 diabetic subjects were GADA−. Other islet autoantibodies, namely IAAs and IA-2As, were not tested for at entry into the study because of their reported low frequency in LADA. Subjects known to have secondary forms of diabetes were excluded. All subjects underwent a structured interview (appendix) to retrospectively determine the clinical features of presentation. The study was approved by the Royal Melbourne Hospital Human Research and Ethics Committee and subjects participating provided written informed consent.
Prospective study

Subsequently, a prospective study was performed on 130 subjects (aged 30–75 years) with recently diagnosed (<2 months) diabetes according to World Health Organization criteria who did not require insulin treatment. Subjects were recruited from a national diabetes register, the National Diabetes Services Scheme, which is managed by Diabetes Australia. Subjects registering with the National Diabetes Services Scheme have the option of agreeing to be contacted for the purpose of research. All subjects eligible for the study (i.e., aged 30–75 years, who did not require insulin at diagnosis) were sent a letter inviting them to participate in the study. Subjects who agreed to participate in the study provided written consent. After a structured interview, patients had blood taken to determine GADAs. The study was approved by the Royal Melbourne Hospital Clinical Research and Ethics Committee.
GADA assay

GADAs were measured by precipitation of in vitro–transcribed and –translated [35S]methionine-labeled GAD65. The assay has had good sensitivity and specificity in International Workshops and Standardization Programs conducted by the Immunology of Diabetes Society (e.g., in ref. 15). Specificity and sensitivity in the 2003 Diabetes Antibody Standardization Program were 97 and 80%, respectively. The threshold for GADA positivity was established as the 97th percentile of unselected healthy schoolchildren at 5 units/ml.

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05Mar

Foods to Avoid When You Have High Blood Sugar

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When there is talk of blood sugar, usually doctors think of glycogen, which is the fuel source the body uses to power all functions. It is derived from glucose, which is produced in the liver which transforms it form different sources such as body fat or carbohydrates, which in turn can be found in all kinds of food such as bread or pasta.

It stands to reason then that the foods you eat will influence your blood sugar, as in the spectacular case of “baguette”, the famous French white bread that causes an immediate spike in the blood sugar because of its staggeringly high 98 on the GI (Glycemic Index) list.

When one is a type 2 diabetic like me, that is not a matter to brush off lightly, although today, I need to say that I am a recovering type 2 diabetic, which I have been for the last 20 years until I discovered that changing my eating habits could help me beat this condition and so I did. When I think that I was risking blood clots, infections, heart diseases, blindness, nerve damage and kidney failure I wonder why I did not decide earlier to love my health better than the stuff in my plate!

Some of my favorite blood sugar lowering foods include anything that is deep green and comestible and garlic these days. I must also mention the natural benefits in this area of Bitter Melon, Fenugreek or Banaba leaf extract, as they help combat hyperglycemia, the other word for high blood sugar levels.

Foods types to avoid when one suffers from the condition because they raise blood sugar levels are juices, milk, carbohydrates, starches and carbohydrates but I must balance this out by saying that most spikes can be avoided by a combination of added protein and exercise, this can be a simple 10 minute walk, like taking out the dog. The extra benefit of combining these is that one also regulates cholesterol levels.

Other food types that help lower blood sugar: cinnamon, strawberries, which I use a lot in my recipes, oatmeal and any veggie that doesn’t contain starch.

Keep your blood sugar levels in check by eating three to five vegetable servings every day.

So, aside from exercise and paying attention to what combination of foods you eat, do not forget to drink a lot of water.

Keeping to foods that are low on the glycemic index list is always a good idea and it is also known that Rye, Quinoa, brown rice, barley and Pumpernickel will help balance blood sugar levels.
Bob Pernula, also known as Diabetes Bob on YouTube, has been a diabetic for the last 20 years and he beat his diabetes condition by changing his eating habits. He is convinced anyone can beat diabetes if they know how and so can you.

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