Study of Insulin Responses to Carbohydrate and Noncarbohydrate Challenges In Insulin-Based Care of Metabolic Disorders

by Majid Ali, MD; Sabitha Dasoju, MB, BS; Naila Karim, MD; J. Amin; and Daawar Chaudhry

We present our initial experience with measurements of insulin responses to carbohydrate and noncarbohydrate challenges for patient education and improved compliance to insulin-focused integrative plans for insulin modification and reversal of diabetes type 2. Predominantly carbohydrate meals produce blood glucose spikes, which trigger insulin spikes. Such changes are not observed with predominantly noncarbohydrate meals. Measurements of such insulin responses, designated insulin responses ratio (IRR), provide for insights into the meal–insulin dynamics and a deeper understanding of crank-and-crankshaft model of insulin receptor dysfunction and its clinical significance.1–6

The study included 30 consecutive adult patients with chronic metabolic, inflammatory-immune, and degenerative disorders who underwent IRR testing. The study data, though limited, offer an opportunity to assess the benefits of insulin-focused patient education and care, shifting from the prevailing glucose-focused clinical discourse.

The study data also allow exploration of any relationship that might exist between increasing IRR values and worsening degrees of hyperinsulinism and diabetes type 2. Specifically, what light, if any, might such a relationship shed on insulin receptor and pancreatic beta cell dynamics that would deepen the patients’ understanding of insulin homeostasis in health and disease?

The term insulin responses ratio (IRR) was coined by one of the authors (MA) for the ratio between blood insulin concentrations measured 1 hour after 75 grams glucose and a 300-calorie noncarbohydrate load.7 We used protein powder, lecithin, ground flaxseed, and organic vegetable juice for the 300-calorie noncarbohydrate load. For some years, we have employed the IRR values for: (1) an initial assessment of insulin homeostasis status of the patient; (2) a simple, easy-to-understand, and objective metric for patient education; (3) improving the patient compliance to integrative plans for hyperinsulinism modification and diabetes reversal plans; and (4) establishing the crucial importance of insulin homeostasis for health preservation, reversal of chronic diseases, and healthful aging.

Hyperinsulinism modification and reversal of diabetes type 2 require a “food philosophy” based on a deeper understanding of cellular bioenergetics and insulin homeostasis. The necessary dietary, detox, and lifestyle changes for success usually take several months. There is a need for a clear, easy-to-understand metric for the patient’s individualized metabolic responses to fats, proteins, and carbohydrates in the dietary plan. The IRR value seems suitable for this purpose and in our early experience materially improved patient compliance.

Results

Tables 1 through 3 present the results of the IRR test for three patients: first with mild hyperinsulinism, the second with severe hyperinsulinism, and the third with diabetes type 2.

Table 1: Insulin and Glucose Profiles with Insulin Responses to 75

Gram Glucose (Upper) and 300-Calorie Noncarbohydrate (Lower) Challenges of a

52-Year-Old 5′ 2″ Woman Weighing 228 Lbs. Presenting with Recurrent Sinusitis, Hypothyroidism, Chronic Fatigue, and Urticaria.

Fasting 1 Hr 2 Hrs 3 Hrs
Insulin 6 50 50 10
Glucose 85 92 87 52
Insulin and Glucose Responses to a 300-Calorie Noncarbohydrate Load
Fasting 1 Hr Insulin Responses Ratio (IRR)
Insulin 14 20 2.5
Glucose 97 83

Table 2: Insulin and Glucose Profiles with Insulin Responses to 75

Gram Glucose (Upper) and 300-Calorie Noncarbohydrate (Lower) Challenges of a

71 Year-Old 5’2″ Woman Weighing 175 Lbs. Presenting with Rapid Weight Gain,

Hypothyroidism, and Prehypertension.

Fasting 1 Hr 2 Hrs 3 Hrs
Insulin 5.8 60.1 36.3 53
Glucose 87 91 76 51
Insulin and Glucose Responses to a 300-Calorie Noncarbohydrate Load
Fasting 1 Hr Insulin Responses Ratio (IRR)
Insulin 4.73 17.7 3.3
Glucose 98 98

Table 3: Insulin and Glucose Profiles with Insulin Responses to 75

Gram Glucose (Upper) And 300-Calorie Noncarbohydrate (Lower) Challenges of a

72-Year-Old 5′ 6″ Woman Weighing 165 Lbs. Presented

with Diabetes, Hypertension, Arthritis.

Fasting 1 Hr 2 Hrs 3 Hrs
Insulin 35 65 55 55
Glucose 155 236 305 281
Insulin and Glucose Responses to a 300-Calorie Noncarbohydrate Load
4/27/14 Fasting 1 Hr 2 Hrs IRR
Insulin 7.4 N/D 9.7 6.7
Glucose 155 174

Table 4:

Distribution of IRR Values of

18

Patients In

3

Groups with Peak Blood Insulin Concentrations (In uIU/mL) of: (1) up to 60; (2) 61

to 200;

(3) over 200.

Patient # Peak Glucose (mg/dL)

Peak Insulin Post Glucose

(uIU/mL)

Peak Insulin Post Nonglucose

(uIU/mL)

IRR Major Diagnoses
Insulin Category 1 with Peak Concentration Below 60 uIU/mL, Mean IRR 3.8
1 78 18.1 <2 9 Allergy, IBS, Eczema
2 100 24.6 7.8 3.1 GERD, Anxiety, Fatigue, Allergy
3 146 51.1 21.86 4.2 Atrial Fibrillation, CFS, BPH
4 117 38.3 11.0 3.4 Colitis, Fatigue, Arthralgia. Allergy
5 82 49 <2 1.7 GERD, Anxiety, Fatigue, Sinusitis
6 82 48 <2 1.7 Allergy, Myalgia. Headache
7 131 37.7 15.3 3.5 Anxiety, Mold Allergy, Headache
8 163 54 9.2 3.0 Allergy, Memory loss, UTI
9 178 54.6 17.7 3.2 Hypothyroid, Prehypertension
10 92 50 10 5 Sinusitis, Urticaria, Hypothyroidism
Insulin Category 2 with Peak Insulin Concentration Between 60 and 200 uIU/mL, Mean IRR 8.2
1 87 69 6 11.5 Colitis, Cystitis, Hypothyroidism
2 81 69 7 10 Rosacea, Eczema, Fatigue, Hypothyroidism, Backache
3 136 86.7 5.6 15.5 Neuropathy, Fatigue, Hypertension
4 161 125 23.5 5.3 Neuropathy, Hypertension, CAD* Allergy
5 165 132 44 5.3 CAD,* Hepatitis C, Neuropathy
6 178 84.7 25 2.1 Weight gain, Neuropathy, Eczema
Insulin Category 3 with Peak Concentration Over 200 uIU/mL, Mean IRR 3.0
1 109 218 87.2 2.5 Diabetes, Anxiety, Hypertension,
2 112 230 63 3.5 Weight Gain, Fatty Liver, Neuropathy

* Coronary Artery Disease

Table 5: Distribution of IRR Values of

18

Patients with Diabetes Type 2. Blood Glucose and Insulin Values Are Expressed in mg/dL and uIU/mL respectively. Mean IRR 7.0

Patient Peak Glucose Peak Insulin Post -Glucose Peak Insulin Post Non-Glucose IRR Major Diagnoses
1 399 29.5 15.5 2.3 Diabetes Type 2, CAD,* Hypertension, Fatigue, Leg edema
2 334 57 24 2.3 Diabetes , Cancer Prostate, GERD
3 326 44.9 4.6 7.3 Diabetes Type 2, CAD,* Arthritis,
4 313 79 5.6 15.5 Diabetes Type 2, CAD,* Blood creatinine 2.6mg/dL
5 305 65 9.7 6.7 Diabetes Type 2, Hypertension, arthritis
6 242 41 3.3 12.4 Diabetes, Prehypertension, Obesity
7 217 100 29.5 3.4 Diabetes Type 2, Headache, Prehypertension
8 213 125 23.5 5.3 Diabetes, Type 2 Colonic Diverticulitis, IBS
9 205 119 14.8 8.0 Diabetes Type 2, CAD*, Hypertension, Hepatic Steatosis, and Neuropathy

Discussion

From an evolutionary perspective of cellular energy economy, the lowest insulin concentrations associated with unimpaired glucose tolerance can be considered as optimal insulin homeostasis. Therefore, the optimal management of the insulin-resistance-hyperinsulinism-diabetes spectrum should be focused on insulin dynamics. In reality, in the prevailing medical model, insulin resistance and hyperinsulinism are completely ignored. (How can it different unless proper insulin testing is done?) As for diabetes type 2, it is treated with drugs that lower blood glucose levels by increasing insulin activity. So, the treatment compounds the underlying problems of hyperinsulinism.

Shifting from Sugar-Talk to Insulin Conversations

As discussed at length in previous publications from our center, hyperinsulinism modification and reversal of diabetes type 2 requires “insulin conversations.”1–9 Within this broader context, there are the matters of dietary, environmental, detox, and spiritual components of integrative plans focused on restoring insulin receptor function, beta cell dynamics, and related aspects of insulin homeostasis. We introduced IRR measurements in our clinical practice in order to expand the range of such conversations, underscoring the need for a shift away from “sugar problems.”

Patient Rating of the IRR Test

We expected that explanation of the mechanics of the IRR test and the effort required to complete the study would deepen the patient’s interest in learning about insulin dynamics in health, hyperinsulinism, and diabetes Type 2. This indeed was the case. A comparative study of a patient’s glucose and insulin profiles with selected examples from our IRR files allowed us to discuss in simple terms the matters of the pathogenesis and reversal of the hyperinsulinism-diabetes continuum with improved patient compliance.

In actual practice in the study, the IRR data were discussed with patients in two successive visits and they were given appropriate write-ups and lent DVDs on the subject suitable for home study. In the third visit, patients were asked to rate the value of the test in: (1) understanding the relationships between types of foods consumed and the blood sugar and insulin responses; and (2) its influence on their food choices. Only 4 of 30 patients asked for further clarification of the test in subsequent visits.

Dietary Plans for Insulin Modification

In our experience, the prevailing notion of counting calories, caloric intake of various food items is not the critical issue in hyperinsulinism modification and diabetes reversal. Rather, attention should be focused on: (1) how different foods in different combinations create sugar spikes with consequent insulin spikes; and (2) how such spikes create undesirable hunger responses, as well as sugar and carbohydrate craving. Specifically, what is needed is the knowledge of how the healthy fats and proteins can be combined with limited amounts of carbohydrates and fruits to prevent or attenuate sugar and insulin spiking. For example, a slice of toast generates a sugar spike but not when it is eaten with an egg. A snack of blueberries, notwithstanding the benefits of berries, generates sugar and insulin spikes, which can be prevented or attenuated when cheese is added to the snack.

Correlation of IRR Value with Degree of Hyperinsulinism

The data in Tables 1 through 3 suggest a correlation between increasing degrees of hyperinsulinism and rising IRR values. This correlation is supported by additional data presented in Tables 4 and 5. In Table 4, mean IRR values in insulin groups 1 and 2 (low-insulin and moderate-insulin groups) are 3.8 and 8.2 respectively. The mean IRR value of the diabetes group of 7 is consistent with the relationship between the carbohydrate and noncarbohydrate responses. The low (3) IRR value in the third insulin group (only 2 patients with extreme hyperinsulinism) is not consistent and may point to as yet unrecognized aspect of such hyperinsulinism. Clearly no inferences can be drawn from just two case studies.

To our knowledge, no studies of relationship between insulin responses to carbohydrate and noncarbohydrate responses have been reported. However, this correlation is not unexpected in light of the crank-and-crankshaft model of insulin resistance and hyperinsulinism – the greater the resistance of insulin receptor embedded in the cell membrane, the larger the expected differential between insulin responses to glucose and noncarbohydrate challenges.1

Glycemic Index

The knowledge of glycemic indices of foods and glycemic loads of meals are very valuable for the general education of the patient. However, these values do not reveal anything about the insulin homeostasis status of the patient, which must be the focus in reversing hyperinsulinism and diabetes.

The value of glycemic indices in metabolic studies has been decried by some influential writers. To cite one recent example, consider the following telling text from the conclusion section of a recent JAMA report on the subject of glycemic index: “In this 5-week controlled feeding study, diets with low glycemic index of dietary carbohydrates, compared with high glycemic index of dietary carbohydrates, did not result in improvements in insulin sensitivity, lipid levels, or systolic blood pressure. In the context of an overall DASH-type diet, using glycemic index to select specific foods may not improve cardiovascular risk factors or insulin resistance.”10

Many readers of Townsend Letter who practice integrated healing arts use glycemic indices and glycemic loads in their clinical work. Such readers might be chagrined by the above citation of the 2014 Harvard study that clearly challenges their use of the index. They are likely to ask, how can any serious student of human nutrition and insulin homeostasis ever think that a mere 5-week study of obese individuals with hypertension (as described in the paper) will yield useful data about the benefits of the use of glycemic indices of foods? For the amusement of such Townsend readers, we include below an excerpt from an op-ed article published in the New York Times on February 21, 201511:

Bad Diet Advice –

for Decades

The article was titled “The Government’s Bad Diet Advice.” It would have been more appropriate if were titled “Harvard School of Public Health Bad Diet Advice – for Decades.” No, we do not take a cheap shot at Harvard here. Consider this text from the same article of the New York Times: “Much of the epidemiological data underpinning the government’s dietary advice comes from studies run by Harvard’s School of Public Health. In 2011, directors of the National Institute of Statistical Sciences analyzed many of Harvard’s most important findings and found that they could not be reproduced in clinical trials. … It’s no surprise that longstanding nutritional guidelines are now being challenged.”

Statistical Sciences analyzed many of Harvard’s most important findings and found that they could not be reproduced in clinical trials!

The Times here is being politically polite; it could have been forthright and stated that Harvard has done a great disservice and should come clean by publically apologizing for having misled the American people for decades.

In closing, hyperinsulinism modification and reversal of diabetes type 2 require a degree of insulin literacy for designing dietary, environmental, detox, and spiritual guidelines for individual patients. There is a need for a clear, easy-to-understand metric for the patient’s individualized metabolic responses to fats, proteins, and carbohydrates in the dietary plan. The IRR value, an objective, quantifiable, and modifiable parameter, seems suitable for this purpose. In our early experience, it materially improved patient compliance.

Notes

1. Ali M. The dysox model of diabetes and de-diabetization potential. Townsend Lett. 2007;286:137–145.

2. Ali M. Insulin responses ratio (IRR) test for hyperinsulinism modification and diabetes type 2 reversal IRR and IRP tests [online article]. DrAli1.org. http://drali1.org/irr_alidiabetes__or.htm.

3. Ali M. Beyond insulin resistance and syndrome X: the oxidative-dysoxygenative insulin dysfunction (ODID) model. J Capital Univ Integr Med. 2001;1:101–141.

4. Ali M. Oxygen, insulin toxicity, inflammation, and the clinical benefits of chelation. Townsend Lett. 2009;315:105–109. October, 2009.

5. Ali M. Insulin reduction and EDTA chelation: two potent and complementary approaches for preventing and reversing coronary disease. Townsend Lett. 2010;323:74–79. June 2010.

6. Ali M. Oxygen, insulin toxicity, inflammation, and the clinical benefits of chelation: part II. Townsend Lett. 2010;323:74–79. June 2010.

7. Ali M. Oxygen, Darwin’s Drones, and Diabetes. Vol. 1, Dr. Ali’s Plan for Reversing Diabetes. New York: Canary 21 Press; 2011.

8. Ali M. Importance of subtyping diabetes type 2. Townsend Lett. April 2014.

9. Ali M. Insulin responses ratio (IRR) test for hyperinsulinism modification and diabetes type 2 reversal IRR and IRP tests [online article]. DrAli1.org. http://drali1.org/irr_alidiabetes__or.htm.

10. Sacks, FM, Carey VJ, Anderson CAM, et al. Effects of high vs low glycemic index of dietary carbohydrate on cardiovascular risk factors and insulin sensitivity. JAMA. 2014;312:2531–2541.

11. Teicholzfeb N. The government’s bad diet advice. New York Times. February 20, 2015.

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