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Study on the Possible Effects of

Prolonged Consumption of

 Ethyl Alcohol on Insulin Resistance

2002

A

DISSERTATION

submitted for the degree of

Doctor of Medicine

(General Medicine & Therapeutics)

to the

UNIVERSITY OF RAJASTHAN, JAIPUR

 

 

Guide: Dr. Kailash Chandra  Jain,                  MD, FICP, FIACM. Professor, Department of Medicine, RNT Medical College, UDAIPUR (Rajasthan) 313 001.

      Anirban Mitra

 

 

 

 

 

 

 

 

Dedicated to

The Patients

 

who, in their suffering,

had helped me in learning medicine

A word of honour

 

Words can hardly express my deep sense of gratitude, indebtedness and reverence for my esteemed teacher and guide Dr. Kailash Jain, MD, FICP, FIACM, Professor, Department of Medicine, RNT Medical College, Udaipur who inspired in me a spirit of dedication, precision and unbiased observation which must be cornerstone of every scientific pursuit.

Without his constant help, masterly guidance, advice, valuable suggestions, deep personal interest and attention, this work would not have taken the present shape.

 

 

 

 

Anirban Mitra

Certificate

 

This is to certify that Dr Anirban Mitra has carried out all the work in connection with his dissertation entitled “Study on the Possible Effects of Prolonged Consumption of Ethyl Alcohol on Insulin Resistance” under my direct guidance and supervision.

The work concerned with the study has been thoroughly carried out by the candidate himself.

I recommend this dissertation for the degree of “DOCTOR OF MEDICINE” (General Medicine and Therapeutics), to the UNIVERSITY OF RAJASTHAN, JAIPUR.

 

 

Dr. Kailash Chandra Jain

MD, FICP, FIACM.

 Professor  & Unit Head

Department of Medicine

R.N.T. Medical College

UDAIPUR (Rajasthan.)

Acknowledgements

 

I owe a deep sense of gratitude to Dr. A.K. Gupta Principal and Controller, R.N.T. Medical College, Udaipur for allowing me to carry out the dissertation work in this institution.

I express my sincere gratitude to the esteemed Physician Dr. B.S. Bomb, Professor and Head of the Department of Medicine, RNT Medical College, Udaipur for his constant encouragement and support.

I am highly grateful to Dr. L.K. Bhatnagar, Professor & Unit Head, Dr. Y.K. Bolya, Associate Professor and Unit Head of Department of Medicine, Dr. S.K. Kaushik, Professor and head Cardiology Unit for permission to include their patient in this study.

Words can hardly express my deep sense of gratitude to my esteemed teachers Dr. D.P. Singh, Associate Professor, and  Dr. P.S. Pipliwal, Assistant Professor, Department of Medicine, R.N.T. Medical College, Udaipur, without whose guidance and profound help this work could not have taken this shape. The abundant interest and attention that they so keenly lavished upon this work has helped it to reach a conclusion.

My sincere thanks to Dr. D.C. Kumawat and Dr. Vijay Goyal,  Associate Professors, Dr. Mahendra Agarwal, Dr. Y.N. Verma, Dr. Mahesh Dave, Dr. R.L. Meena, and Dr. Swati Shrivastava, Assistant Professors, Department of Medicine and Dr D.C. Sharma, Assistant Professor Endocrinology,  RNT Medical College, Udaipur for their co-operation and guidance in carrying out this work.

I express my gratitude to Dr. K.L. Mali, Professor, Department of Biochemistry, for permission to use Clinical Biochemistry Laboratory for this dissertation.

I am extremely thankful to Dr. Surendra Kumar Rajpurohit, Director and the technicians, Mr. Khurshid, Mr. Anil, Mr. Yunus and others of Rajasthan Clinical Research Centre for their laboratory assistance and guidance.

I am highly indebted to my friends and colleagues, Dr. Raghu Prasad, Dr. Raghavendra S, Dr. Ajay Gainda, Dr. Prem Choudhary, , Dr. Kiran Intodia, Dr. Sangeeta Bordia, Dr. Nagesh CM, Dr Jayesh Gandhi, Dr. Bhanwarlal Bohra, Dr. Harish Sharma, Dr. Prabhat Kanwaria, Dr. Guliver, Dr. Sushil Chauhan whose practical advice and apt comments were often of great help in forming a perspective of the work.

It is impossible for me to quantify and express in words my gratitude for my parents, Dr Rabi Mitra and Srimati Ashima Mitra,  and my  sister,  brothers, sisters–in-law, brother-in-law who are a constant source of inspiration and encouragement in my life.

I will be failing in my duty if I do not acknowledge the unlimited help extended by the nursing staff of MB Govt. Hospital in carrying out this dissertation.                          

My sincere thanks to all those people known and unknown who have by their courtesy, enthusiasm and ardour helped me re-institute my self-confidence and have been an invaluable aid in heralding the completion of my dissertation.

Last but not the least; I extend my heartfelt thanks to the patients whose consent for inclusion in the study was instrumental in the culmination of my work.

 

 

 

Dr Anirban Mitra

 

 

 

 

TABLE OF CONTENTS

 

Description	Page No.
1. Introduction	1
2. Review of Literature	13
3. Material and Methods	33
4. Observations	43
5. Discussions	56
6. Summary and Conclusions	65
7. Bibliography	68
8. Miscellaneous	73

 

 

 

 

 

 

Introduction

Introduction

Diabetes Mellitus consists of a group of metabolic disorders characterised by hyperglycaemia resulting from defects in insulin secretion, insulin action or both. It is the commonest endocrine disorder in human being. American Diabetes Association¹ has classified diabetes mellitus into four major types and many subtypes according to mechanism of production of hyperglycaemia. In type 2 DM, the condition may range from predominantly insulin resistance with relative insulin deficiency to a predominantly insulin secretory defect with insulin resistance.

Type 2 diabetes mellitus is rapidly emerging as a major public health problem. There are estimated 86 million diabetics in Asia of which a third (25-30 million) are in India.²Â  Prevalence of diabetes mellitus (6.0 in urban as compared to 2.8% in rural populations) was significantly (P<0.001) higher in urban compared to rural subjects in a recent study³ conducted in North India. In another study the age-adjusted prevalence rate was found to be 8.2% in urban and 2.4% in rural population. ⁴ The projected prevalence of diabetes in India by 2005 will be 30 to 35 million and one out of every five diabetic subjects in the world will be Indian. ⁵ Studies in India in the last decade have highlighted that not only is the prevalence of type 2 diabetes high, but that it is increasing within the urban population. A recent national survey of diabetes⁶ conducted in six major cities in India shows that the prevalence of diabetes in urban adults was 12.l%. Prevalence of Impaired glucose tolerance (IGT) was also high (14.0%). Several epiderniological studies by the Diabetes Research Centre, Chennai have shown that the percentage of adult urban subjects affected has increased from 5.2% in 1984 to 8.2% in 1989, 11.6% in 1995 and 13.9% in 2000. ^{7, 8} It is calculated that in 2000 AD approximately about 33 million adults in India will have diabetes.

In rural India the prevalence of type 2 diabetes, is 4-6 limes lower than in urban areas⁸. Hence urgent action is required for proper detection and management of diabetics in India including delineation of its causative factors for adoption of proper long-term preventive measures.

Type 2 diabetes mellitus has a very complex aetiopathogenetic sequence with both genetic and environmental influences playing its part. It has a strong genetic component evidenced by high concordance rate (70 to 90 per cent) in monozygotic twin and increased risk of diabetes in individuals whose either parent is having type 2 diabetes mellitus (up to 40 per cent). Insulin resistance is detected in many non-diabetic first-degree relatives of diabetic persons.  Exact genetic mapping of defects in type 2 diabetes mellitus is yet not achieved. Moreover, genetic defects of insulin secretion or action may not manifest unless another genetic defect (e.g. obesity) or an environmental event is superimposed.

Type 2 diabetes mellitus is characterised by three pathophysiologic abnormalities: peripheral insulin resistance, impaired insulin secretion and excessive hepatic glucose production. Obesity, particularly central, is commonly associated with type 2 diabetes mellitus, which further augments insulin resistance. Initially there is a hyperinsulinaemic state with normal glucose tolerance. Ultimately compensatory mechanism of β cells fails and patient develops impaired glucose tolerance followed by frank diabetes. The pathophysiology of type 2 diabetes, which accounts for over 90% of patients with the disease, involves defects in three organ systems that conspire together to produce abnormal glucose and lipid metabolism. While there is some uncertainty regarding the primary lesion, or relative importance of different tissues, metabolic defects in liver, peripheral target tissues such as fat and muscle and pancreatic β cells all contribute to the syndrome. Insulin resistance, which is defined as a state of reduced responsiveness to normal circulating concentrations of insulin, is now recognized as a characteristic trait of type 2 diabetes, and contributes to abnormalities in all of these tissues. A number of prospective epidemiological studies across several population groups have indicated that type 2 diabetes progresses over a continuum of worsening insulin action, beginning with peripheral insulin resistance and ending with a loss of insulin secretion. In most patients, insulin resistance can be detected long before the deterioration of glucose intolerance occurs. Insulin resistance is a quite common state, associated with aging, a sedentary lifestyle, as well as a genetic predisposition. The state seems to be fuelled by or perhaps to a certain extent the result of obesity. The ensuing dysregulation of carbohydrate and lipid metabolism that occurs as a consequence of insulin resistance further exacerbates its progression. Beta cells of the pancreas normally compensate for the insulin-resistant state by increasing basal and postprandial insulin secretion. At some point, the beta cells can no longer compensate, failing to respond appropriately to glucose. This ultimately leads to the deterioration of glucose homeostasis, and the development of glucose intolerance.

Approximately 5 -10% of glucose intolerant patients per year progress to frank diabetes, which continues to worsen as insulin resistance increases. Adipose cells generate more fatty acids, the liver produces more glucose in an unregulated fashion, and the beta cells undergo complete failure, resulting in the late stages of the disease, where high doses of exogenous insulin may be required. Even in the absence of diabetes, insulin resistance is a key feature of other human disease states. Impaired insulin action coupled with hyperinsulinemia leads to a variety of abnormalities, including elevated triglycerides, low levels of HDL, enhanced secretion of VLDL, disorders of coagulation, increased vascular resistance, changes in steroid hormone levels, attenuation of peripheral blood flow and weight gain. Thus, insulin resistance is often associated with central obesity, hypertension, polycystic ovarian syndrome, dyslipidemia and atherosclerosis. This constellation of symptoms is often referred to as Syndrome X, or Insulin Resistance Syndrome. Whether impaired insulin action is directly responsible for all of the symptoms in these patients remains unclear. However, the broad prevalence of insulin resistance and its association with profound metabolic abnormalities is widely accepted.

Insulin is the most potent anabolic agent known, promoting the synthesis and storage of carbohydrates, lipids and proteins, and inhibiting their degradation and release back into the circulation. Insulin maintains glucose homeostasis by stimulating glucose uptake, utilization and storage in muscle and adipose tissue, and inhibiting glucose output from liver. The hormone also plays an important role in regulating lipid homeostasis, stimulating lipogenesis in fat and liver, and inhibiting lipolysis in fat and muscle. While the underlying cause of insulin resistance remains unknown, investigations have focused on defects in signalling and metabolic pathways.

Studies in type 2 diabetic patients have shown that the primary defect in insulin action lies in the regulation of glucose transport in adipose and muscle. This process is mediated by the insulin-stimulated glucose transporter⁹, Glut4. Insulin action is initiated through the binding to and activation of its tyrosine kinase receptor. At the cellular level, the action of the hormone is characterized by a diverse variety of effects, including changes in vesicle trafficking, stimulation of protein kinases and phosphatases, promotion of cellular growth and differentiation, and activation, or in some cases, repression of transcription¹⁰.

Insulin resistance is caused by decreased ability of insulin to act on peripheral target tissues (especially muscle and liver). This resistance is relative as supernormal levels of insulin overcomes this resistance and normalise plasma glucose. There is a rightward shift of insulin dose-response curve along with reduced maximal response indicating 30 to 60% decreased glucose utilisation¹¹. There is decreased glucose uptake and usage by insulin sensitive tissues such as muscles causing postprandial hyperglycaemia as well as increased hepatic glucose output leading to fasting hyperglycaemia. Glucose usage in non-insulin sensitive tissues (e.g. brain) is not impaired.

Diabetes mellitus is commonly associated with systolic/diastolic hypertension, and a wealth of epidemiological data suggests that this association is independent of age and obesity. Much evidence¹² indicates that the link between diabetes and essential hypertension is hyperinsulinemia. Thus, when hypertensive patients, whether obese or of normal body weight, are compared with age- and weight-matched normotensive control subjects, a heightened plasma insulin response to a glucose challenge is consistently found. A state of cellular resistance to insulin action subtends the observed hyperinsulinism. With the insulin/glucose-clamp technique, in combination with tracer glucose infusion and indirect calorimetry, it has been demonstrated that the insulin resistance of essential hypertension is located in peripheral tissues (muscle), is limited to non-oxidative pathways of glucose disposal (glycogen synthesis), and correlates directly with the severity of hypertension. The reasons for the association of insulin resistance and essential hypertension can be sought in at least four general types of mechanisms: Na⁺ retention, sympathetic nervous system over-activity, disturbed membrane ion transport, and proliferation of vascular smooth muscle cells. Physiological manoeuvres, such as calorie restriction (in the overweight patient) and regular physical exercise, can improve tissue sensitivity to insulin; evidence indicates that these manoeuvres can also lower blood pressure in both normotensive and hypertensive individuals. Insulin resistance and hyperinsulinaemia are also associated with an atherogenic plasma lipid profile. Elevated plasma insulin concentrations enhance very-low-density lipoprotein (VLDL) synthesis, leading to hypertriglyceridemia. Progressive elimination of lipid and apolipoproteins from the VLDL particle leads to an increased formation of intermediate-density and low-density lipoproteins, both of which are atherogenic. Insulin, independent of its effects on blood pressure and plasma lipids, is known to be atherogenic. The hormone enhances cholesterol transport into arteriolar smooth muscle cells and increases endogenous lipid synthesis by these cells. Insulin also stimulates the proliferation of arteriolar smooth muscle cells, augments collagen synthesis in the vascular wall, increases the formation of and decreases the regression of lipid plaques, and stimulates the production of various growth factors. Insulin resistance appears to be a syndrome that is associated with a clustering of metabolic disorders, including non-insulin-dependent diabetes mellitus, obesity, hypertension, lipid abnormalities, and atherosclerotic cardiovascular disease.

Type 2 diabetes mellitus in Indians is in many ways different in that of Caucasians.  An analysis of epidemiological pattern of study subjects in UK Prospective Diabetes Study ¹³ revealed that Indian patients were younger (mean age 52.3, 47.0, 51.0 years respectively for Caucasians, Indians and Afro-Caribbeans), less obese (BMI 29.3, 26.7, 27.9 kg/m² respectively for Caucasians, Indians and Afro-Caribbeans). Indians had a greater waist-hip ratio, lower blood pressure and lower prevalence of hypertension. They were more often sedentary (39% as compared to 19% of Caucasians and 15% of Afro-Caribbeans), more often abstained from alcohol (55% as compared to 21% in Caucasians and 25% in Afro-Caribbeans) and had a greater prevalence of first-degree relatives with known diabetes (36%, 44% and 34% for Caucasians, Indians and Afro-Caribbeans respectively). Indians had more impaired insulin sensitivity (19% of normal as compared to 27% in Afro-Caribbeans and 23% in Caucasians) by homeostasis model assessment but less severely impaired beta-cell function. (p value < 0.001 for all comparisons.

Another study¹⁴ showed that Asian Indian men are more insulin resistant than Caucasian men independently of generalized or truncal adiposity. The excessive insulin resistance in Asian Indians is probably a primary metabolic defect and may account for the excessive morbidity and mortality from diabetes and coronary heart disease in this population

There is renewed interest in of insulin resistance (or sensitivity) due to introduction of a new class of drug thiazolidinediones (glitazones). These drugs exhibit their action by decreasing insulin resistance at cellular levels acting on Peroxisome Proliferator Activated Receptor g (PPAR). They have shown excellent results in many Indian diabetics. Hence other factors which may modify insulin resistance need to be investigated and assessed. 

Ethanol (C₂H₅OH) is a central nervous system depressant that depresses activity of neurons, though some behavioural stimulation is seen in low doses due to dis-inhibition of higher control. Though alcohol drinking is an accepted social practice in many societies, it is a common substance of abuse. Although alcohol consumption at mild to moderate levels (one to two drinks a day) by otherwise healthy non-pregnant individual has been shown to have some beneficial effect, especially cardiovascular, alcohol in higher doses is toxic to most body system. An ethanol load in a fasting healthy individual is likely to produce transient hypoglycaemia within six to thirty six hours due acute suppressive effects of ethanol on gluconeogenesis. This can result in glucose intolerance. However effect of chronic alcohol intake on glucose intolerance or insulin sensitivity is less well defined¹⁵.

Rising trend of diabetes is becoming a major health problem and matter of grave concern for health authorities, doctors, social workers and the government. Parallel with this rising trend of diabetes, another disturbing rise has been noticed in the trend of alcohol consumption in our country. With the entry of multinational corporations in the market due to liberalisation coupled with lax surveillance rules, the number of people taking to alcohol is projected to increase.

Obtaining reliable prevalence of extent of alcohol abuse in India is difficult because of differences in (a) definition; (b) survey instruments used and (c) population screened between epidemiological studies. However various studies¹⁶ indicate prevalence varying between 25% and 80% in general populations and 10% to 58% amongst students. Another survey¹⁷ done by NIMHANS, Bangalore found almost a quarter (23.3%) of the general hospital  in-patients had associated drinking problems which were more among medical than surgical in-patients. A study by Walia M et al.¹⁸ in New Delhi showed a prevalence of alcohol consumption and/or smoking in 28.6% of men with type 2 diabetes mellitus

A study¹⁹ was conducted on prevalence and social factors of alcoholism in rural areas of Ajmer district in Rajasthan.  The results showed that prevalence of alcohol abuse in the sample was 24.7% (36.1% for males and 13.4% for females) and the percentage of dependence was 3%. Alcohol abuse was found to be significantly associated with religion (higher in Hindus with a relative risk of 8.65 in males and 5.21 in females), marital status (higher in married with a relative risk of 2.51 in males), age (higher in age group more than 20 years with a relative risk of 2.50 in males and 1.63 in females), family structure (higher in nuclear or joint families with a relative risk of 2.88 in males), educational status (higher in illiterates with a relative risk of 1.53 in males) and occupational status (higher in those engaged in agriculture with a relative risk of 1.43 in males and 1.80 in females).In About 50% of both male and female users were between 20 and 39 years of age; 8.1% of males and only 1.3% of females used alcohol daily or several times in a week. Desi (country) liquor was the beverage used by more than 85% of the users; 77.5% of males and 96.5% of females consumed less than one quarter of a bottle of alcohol, and 65.3% of males and 93.6% of females were taking alcohol at their houses only. Hence the quality of alcohol offered to Indian public is a matter of concern to health authorities.

Prolonged alcohol consumption and its relationship with overt manifestations of diabetes have interested scientists throughout the world. Studies had been undertaken to explore this association in Japan²⁰, Sweden²¹, and Italy²².

Hence increasing alcohol usage may be one the “missing link” of increasing insulin resistance in Indian population. Detailed study is warranted to explore this association.

 

OBJECTIVES

The objective of the undertaken study was: -

1.      To measure insulin sensitivity in type 2 diabetics who are moderate to heavy drinker; who are ex-drinker; alcoholics who are non-diabetics and a control cohort who are non-diabetics and non-drinkers.

2.      To compare insulin sensitivity in above mentioned four categories

3.      To attempt to find out relation of anthropometric data such as Body Mass Index (BMI) and Waist-Hip Ratio with insulin sensitivity in all four groups.

4.      To assess effect of alcohol on insulin sensitivity by comparing these four group of patients.

 

 

 

Review of Literature

Review of Literature

In India there is a rapidly escalating epidemic of insulin resistance syndrome (diabetes, hypertension and coronary heart disease). Contribution of genes and environment is under debate. Various factors have been identified for increasing insulin resistance but exact mechanism by which these factors act has not been elucidated.

Anthropometric measurements such as Body Mass Index (BMI) and Waist Hip Ratio (WHR) give a rough estimate of Insulin resistance. Higher values of these indices are usually indicative of decreased insulin sensitivity. Various anthropometric indices have been used to quantify generalised and central obesity. The WHR is the most widely used index of regional adipose tissue distribution and is measured in a standing position. Waist circumference is defined as the minimal circumference measured at the navel, and the hip circumference is defined as the widest circumference measured at the hips and buttocks²⁴.

There is a well documented sex dimorphism in regional adipose tissue distribution²⁵. Indeed, despite the fact that women are usually more obese as a group than men, male subjects more frequently have significantly higher mean waist circumference and higher mean WHR in agreement with the greater propensity of men to accumulate excess fat within the abdominal cavity. Thus, the threshold values suggested by Pouliot et al. ²⁵ of 0.85 for women and 0.95 for men are in agreement with those proposed in previous studies²⁶. Since the WHR has been shown to be associated, albeit moderately, with the amount of abdominal visceral adipose tissue measured by CT or MRI [the "gold standards" for such determination²⁷], this index has been widely used to investigate the relations between regional adipose tissue distribution and metabolic profile. Thus it was effective in predicting aberrations in glucose and insulin levels and also showed a strong correlation between plasma lipids and blood pressure. ²⁸ WHR predicted subsequent diabetes in men29 and coronary heart disease30 and was more predictive of these endpoints than either the BMI or a more complex procedure using the sum of multiple skinfold thickness.

Tai ES et al.³¹ compared body mass index (BMI), waist circumference, waist-hip ratio (WHR) and percentage body fat measure as predictors of fasting lipid profiles and insulin resistance in 109 Singaporean Chinese. BMI was significantly correlated with insulin resistance and there appeared to be a threshold at 26 kg/m2 above which the regression line became steeper. WHR best predicted fasting triglyceride in both men and women. In women, it was inversely correlated with high density lipoprotein cholesterol. A similar association was seen in men but this did not reach statistical significance. The investigators concluded that measurement of BMI and WHR should be part of the assessment of cardiovascular risk in any population as they connote different aspects of risk.

The association of insulin with cardiovascular disease (CVD) may be mediated in part by the associations of insulin with CVD risk factors, particularly blood pressure and serum lipids. These associations were examined in 4576 black and white young adults in the CARDIA Study ³². Fasting insulin level was correlated in univariate analysis with systolic blood pressure (r = 0.16), diastolic blood pressure (r = 0.13), triglycerides (r = 0.27), total cholesterol (r = 0.10), high density lipoprotein (HDL) cholesterol (r = -0.25), and low density lipoprotein (LDL) cholesterol (r = 0.14), and with age, sex, race, glucose, body mass index, alcohol intake, cigarette use, physical activity, and treadmill duration (all p less than 0.0001). After adjustment for these covariates, insulin remained positively associated with blood pressure, triglycerides, total and LDL cholesterol, and apolipoprotein B and was negatively associated with HDL, HDL2 and HDL3 cholesterol, and apolipoprotein A-I in all four race-sex groups. Higher levels of fasting insulin are associated with unfavorable levels of CVD risk factors in young adults.

Walia et al. of RML Hospital, New Delhi conducted a cross sectional study¹⁸ to find the prevalence of coronary risk factors in type 2 diabetes mellitus patients and compared and correlated these risk factors in type 2 diabetics with and without electrocardiographic and/or symptomatic evidence of coronary heart disease (CHD). They found that mean age of patients was 53.12 year and 8.86 year was the mean duration of diabetes. 28.6% of the diabetic men were found to be currently smoking and/or consuming alcohol, 82% were involved in sedentary physical activity and 20.4% had family history of CHD. Central obesity was observed in 46.7% of the cases; more so in females. 31.74% of cases were hypertensive; more females than males had hypertension (33.8% vs. 30%). Poor glycaemic control (HbA1c > 9.5%) was seen in 16.8% of the cases. In about 52.5% of the total group hypertriglyceridemia was noted. Microalbuminuria could be found in 35.93%. CHD was diagnosed in 15.57% of cases in this study.

Insulin sensitivity is measured by various techniques. The hyperinsulinaemic euglycaemic glucose clamp technique as described by DeFronzo et al.³³ is the "gold standard" for quantifying insulin sensitivity in vivo because it directly measures the effects of insulin to promote glucose utilisation under steady state conditions. However, the glucose clamp is not easily applied in clinical settings because intravenous infusion of insulin, frequent blood sampling over a 3-h period, and continuous adjustment of a glucose infusion are required for each subject studied. A well-accepted alternative for estimating insulin sensitivity involves minimal model analysis³⁴ of a frequently sampled IV glucose tolerance test (FSIVGTT). But this requires obtaining approximately 30 blood samples over three hours. Furthermore, although the minimal model index of insulin sensitivity (SI_MM) obtained by this method generally correlates with glucose clamp measurements, identification of SI_MM in subjects with impaired insulin secretion (e.g. patients with diabetes) is often problematic. Hence need for developing a simple and effective surrogate measurement was felt by many investigators. Fasting insulin is presumed to be a surrogate measure of insulin resistance. It had been used in few epidemiological studies as a measure of insulin resistance. Another measure of insulin resistance devised by Matthews et al. called “Homeostasis Model Assessment (HOMA)” depended on relationship between fasting blood sugar and fasting insulin based on a mathematical model. This measure had been used in various population trials including UKPDS. According to this model Insulin resistance is measured by the formula, HOMA-IR= G₀ ✕ I₀ /22.5 and β-cell function is measured by the formula, HOMA-BCF= (20 ✕ I₀) / (G₀ – 3.5), where G₀ is fasting glucose concentration in millmole per litre and I₀ is fasting insulin concentration in µu/ml.

   Katz et al.³⁶ of National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland devised a Quantitative Insulin Sensitivity Check Index (QUICKI) based on fasting values of insulin and glucose only and is obtained by the formulae

QUICKI =1 / [log₁₀ (Insulin₀) + log₁₀ (Glucose₀)]

where Insulin₀ indicates fasting Insulin level and Glucose₀ indicates fasting glucose level.

They found that the index correlates well (Correlation coefficient, r=0.78) with insulin sensitivity determined by euglycaemic clamp method.

 Meta-analysis³⁷ of studies of Insulin Resistance showed simple mathematical combinations of fasting insulin and glucose measures (QUICKI) provide estimates of insulin sensitivity with variability and discriminant power comparable to those of euglycemic hyperinsulinaemic clamps and superior to measures based on insulin alone. In accounting for both the glucose and insulin levels, these measures are more generalisable to the full range of metabolic conditions associated with insulin resistance. This underlies the excellent correlations of these measures with clamps seen in obese and diabetic insulin-resistant subjects. Furthermore, changes in insulin sensitivity can be demonstrated using these tools in comparatively small groups of subjects.

Alcohol is known to cause hypoglycaemia in normal persons. However, Christiansen C et al.³⁸ showed that ethanol caused no change in blood glucose or insulin concentrations in type 2 diabetics. The FFA level was suppressed by ethanol while the triacylglycerol level was unaffected. The insulin sensitivity as measured by euglycaemic clamp method was not affected by ethanol. No major acute effect of ethanol on the glycaemic control in fasting type 2 diabetic patients was found in comparison with what is seen in healthy people

In experimental animals effect of ethanol on insulin release has been measured. Patel and Singh³⁹ found that ethanol inhibits glucose mediated insulin release in perfused rat islet cells in a dose dependent manner.

An important factor affecting glycaemic control in diabetics who are alcoholics is poor diet and drug compliance. In a study⁴⁰done  amongst in-city minorities in Los Angeles it was found drinking any alcohol-containing beverage within 30 days was associated with poorer adherence to prescribed dietary recommendations for the consumption of fibre (t = 2.4; P< 0.05), fat (t = 4.2; P< 0.01), sweets (t = 2.7; P<0.01), and energy (calories) (t = 2.0; P< 0.05). Drinkers were also less likely to exercise for at least 20 minutes per day (t = 2.2; P< 0.05), comply with oral medication regimens (t = 4.6; P< 0.01), or attend outpatient follow-up visits (r = -0.11; P< 0.05). Alcohol use did not significantly alter compliance with home glucose monitoring, insulin use, or haemoglobin A1c levels, although there was a trend toward higher haemoglobin A1c levels among drinkers (11.0 vs. 10.4). Multivariate analysis of the data demonstrates that when demographic characteristics, health care utilisation, and other diabetes-related variables are held constant, the relation between alcohol use and dietary compliance remained significant.

Various studies have shown conflicting results as far as effect of chronic alcohol intake on glycaemic status and insulin resistance is concerned.

In a randomised, multicentre, 12-month parallel open-label study⁴¹ comparing the clinical safety and efficacy of insulin lispro with regular human insulin, it was found that associated hypoglycaemia risk was lower with increased alcohol consumption.

Solomon CG et al.⁴² assessed prospectively the association between moderate alcohol intake and coronary heart disease risk in women with type 2 diabetes mellitus, a group at high risk for cardiovascular disease. They studied women in the Nurses' Health Study who reported a diagnosis of diabetes mellitus at > 30 years of age. During 39,092 person-years of follow-up from 1980 to 1994, there were 295 coronary heart disease events documented among this population, including 194 cases of nonfatal myocardial infarction and 101 cases of fatal coronary heart disease. Odds ratios derived from logistic regression were used to estimate Relative Risks for coronary heart disease as a function of usual alcohol intake, with adjustment for potential confounding factors. Compared with diabetic women reporting no alcohol intake, the age-adjusted relative risk for nonfatal or fatal coronary heart disease among diabetic women reporting usual intake of 0.1 to 4.9 g (<0.5 drinks) of alcohol daily was 0.74 (95% confidence interval = 0.56 to 0.98). Among those reporting usual intake > 5 g/d, it was 0.48 (95% confidence interval 0.32 to 0.72) (P for trend <0.0001). Inverse associations between alcohol intake and coronary heart disease risk remained significant in multivariate analysis adjusting for several other coronary risk factors. For alcohol intake of 0.1 to 4.9 g/d, the Relative Risk was 0.72 [95% confidence interval 0.54 to 0.96] whereas for intake of 5 g/d or more the Relative Risk was 0.45 [95% CI = 0.29 to 0.68]). The investigators concluded although potential risks of alcohol consumption must be considered, these data suggested that moderate alcohol consumption is associated with reduced coronary heart disease risk in women with diabetes and should not be routinely discouraged_­.

Valmadrid CT et al. in their prospective population based cohort study with a mean follow up period of 12.3 years conducted in Winconsin ⁴³ found that alcohol use was inversely associated with risk of Coronary Heart Disease(CHD) mortality in older onset diabetic subjects. The CHD mortality rates for never and former drinkers were 43.9 and 38.5 per 1000 person years, respectively, while the rates for those with alcohol intakes of less than 2, 2 to 13, and 14 or more g/d were 25.3, 20.8, and 10.0 per 1000 person years, respectively. Compared with never drinkers and controlling for age, sex, cigarette smoking, glycosylated haemoglobin level, insulin use, plasma C peptide level, history of angina or myocardial infarction, digoxin use, and the presence and severity of diabetic retinopathy, former drinkers had a relative risk (RR) of 0.69 (95% confidence interval [CI] 0.43- 1.12). For those who drank less than 2 g/d (less frequent than 1 drink a week), the RR was 0.54 (95% CI, 0.33 0.90); for 2 to 13 g/d, it was 0.44 (95% CI, 0.23 0.84); and for 14 or more g/d (about 1 drink or more a day), it was 0.21 (95% CI, 0.09 0.48). Further adjustments for blood pressure, body mass index, education, physical activity, diabetes duration, hypertension history, overt nephropathy, peripheral neuropathy, lipid measures, or intake of medications such as aspirin and anti-hypertensive agents did not change the associations observed. These results suggested an overall beneficial effect of alcohol consumption in decreasing the risk of death due to CHD in people with older onset diabetes.

Relationships between alcohol use and Insulin Sensitivity Index (SI) and cardiovascular disease risk factors were assessed by Bell et al.⁴⁴ in a cross-sectional analysis of 1,196 white, African-American, and Hispanic men and women from the Insulin Resistance and Atherosclerosis Study (IRAS). Five categories of previous-year alcohol use (never, <0.5 drinks/day, 0.5-0.99 drinks/day, 1-2.99 drinks/day, and > or =3 drinks/day) and log SI + 1 (frequently sampled intravenous glucose tolerance test with Bergman minimal model analysis), log fasting insulin, log triglyceride, HDL cholesterol, and systolic/diastolic blood pressure were examined using analysis of variance. In this study, univariate analysis showed an inverse U-shaped relationship between SI and alcohol intake, with a peak at the 0.5-0.99 drinks/day category. A U-shaped relationship was observed between fasting insulin and the lipid and blood pressure measures. After adjustment for demographic (clinic, sex, ethnicity, age), lifestyle (smoking, dietary energy/fat intake, physical activity), and physical (BMI, waist circumference) variables, the alcohol/insulin association was attenuated, but the association with lipids and blood pressure remained for high-intake categories. These data suggested that the enhanced SI associated with light-to-moderate alcohol consumption might be a function solely of a BMI and central adiposity profile more favourable to higher SI.

 

During Osaka Health Survey²⁰ in Japan, the investigators enrolled 6,362 Japanese men aged 35-61 years who did not have diabetes, impaired fasting glucose, hypertension, or liver cirrhosis at study entry. Type 2 diabetes was defined as a fasting plasma glucose (FPG) level > or =126 mg/dl or was diagnosed by a physician. Data on alcohol consumption were obtained from questionnaires. The investigators confirmed 456 cases of type 2 diabetes during the 62,016 person-years of follow-up. It was found that the relationship between daily alcohol consumption and the risk of type 2 diabetes among lean men and among men with a higher BMI was paradoxical. Among lean men (BMI < or =22.0 kg/m2), heavy drinking was associated with an increased risk of type 2 diabetes. Men who consumed > 50.1 ml/day of alcohol had a relative risk (RR) of 2.48 (95% CI 1.31-4.71) compared with non-drinkers after adjusting for age, BMI, regular physical exercise, parental history of diabetes, smoking habits, and FPG level. However, among men with a BMI >22.1 kg/m2, moderate drinking (29.1-50.0 ml/day) was associated with a decreased risk of type 2 diabetes. Daily moderate drinkers had a multiple adjusted Relative Risk of 0.58 (95% confidence interval 0.39-0.87) compared with non-drinkers. It was concluded that among men with a BMI > 22.1 kg/m2, moderate alcohol consumption was associated with a reduced risk of type 2 diabetes, but among lean men (BMI < 22.0 kg/m2), heavy alcohol consumption was associated with an increased risk of type 2 diabetes.

Another population-based cross-sectional study²¹ consisting of 3,128 Swedish men, aged 35-56 years investigated the association between alcohol consumption and impaired glucose tolerance and Type 2 diabetes mellitus. Oral glucose tolerance testing identified 55 cases of Type 2 diabetes and 172 cases of impaired glucose tolerance. Information on alcohol consumption, family history of diabetes, smoking and physical activity was obtained by questionnaire. After adjustment for family history, smoking, physical activity and body mass index, the odds ratio of diabetes was 2.1 (95% confidence interval [CI] 1.0-4.5) in men with high consumption of alcohol (corresponding to over 12 drinks per week) and 0.7 (0.3-1.8) in moderate consumers (7-12 drinks), compared to occasional drinkers. For impaired glucose tolerance, the corresponding odds ratios were 0.7 (0.5-1.1) and 0.6 (0.4-1.0), respectively. Separate analyses for type of beverage indicated that high consumers of beer, spirits and wine had an odds ratio for diabetes of 2.9 (1.2-6.9), 3.3 (1.4-7.8) and 1.2 (0.5-2.7), respectively. The results indicated that high consumption of alcohol increases the occurrence of Type 2 diabetes and that this may primarily concern consumption of beer and spirits. For impaired glucose tolerance, regular alcohol consumption was associated with a reduced prevalence, particularly at moderate levels.

In a large prospective and cross-sectional study, called Bruneck Study²² done in Bruneck, Bolzona province, Italy, relation between regular alcohol intake and insulin sensitivity was assessed in 820 healthy men and women.   The study showed that the fasting insulin concentrations were 12.4, 10.0, 8.7 and 7.1 µU/ml in non-drinkers, subjects reporting drinking of low (1-50 g/d), moderate(51-99 g/d) and heavy (>100 g/d) respectively (p<0.001). The changes were independent of sex, BMI, smoking, medication and diet. The investigators concluded that low to moderate amount of alcohol, when consumed on a regular basis, improves insulin sensitivity. Insulin was thought to be intermediate in alcohol consumption and metabolic syndrome.

Singh et al.⁴⁵ found the plasma insulin and C-peptide responses to glucose were delayed in diabetic patients compared to controls but were not affected by ethanol. In vitro, ethanol at a concentration of 100 mg/dl or greater, significantly decreased insulin binding to erythrocytes in a dose-related manner. Scatchard analysis of competitive insulin binding to erythrocytes indicated that ethanol reduced insulin binding affinity but not binding capacity.

Among the nondiabetic participants of the Kaiser Permanente Women Twins Study⁴⁶ (1989 through 1990), within the range of light to moderate drinking habits, alcohol consumption was inversely related to fasting and postload insulin levels. This relation did not explain associations of alcohol intake with lipid levels and might instead reflected an additional mechanism by which moderate alcohol consumption impacts cardiovascular disease risk.

Recently in a randomized controlled crossover trial⁴⁷ of 63 healthy postmenopausal women, conducted at a clinical research centre in Maryland between 1998 and 1999, participants were randomly assigned to consume 0, 15, or 30 g/d of alcohol for 8 weeks each as part of a controlled diet. All foods and beverages were provided during the intervention. An iso-caloric beverage was provided in the 0-g/d arm. Energy intake was adjusted to maintain constant body weight. A complete set of plasma samples was collected and analyzed for 51 women who completed all diet treatments. Consumption of 30 g/d of alcohol compared with 0 g/d reduced fasting insulin concentration by 19.2% (p = .004) and triglyceride concentration by 10.3% (p = 0.001), and increased insulin sensitivity by 7.2% (P = .002). Normal-weight, overweight, and obese individuals responded similarly. Only fasting triglyceride concentration was significantly reduced when comparing 0 and 15 g/d of alcohol (7.8%; P = .03), and no difference was found between consumption of 15 and 30 g/d of alcohol; however, there was a significant linear trend (P = .001). Fasting glucose concentrations were not different across treatments. Investigators concluded that consumption of 30 g/d of alcohol (2 drinks per day) has beneficial effects on insulin and triglyceride concentrations and insulin sensitivity in nondiabetic postmenopausal women.

Kornhuber HH et al. ⁴⁸ investigated the relationship between alcohol consumption, the "liver enzymes" and other metabolic parameters, including the serum lipids in 1214 adult persons. In 798 of the persons, glucose tolerance tests with measurement of plasma insulin were performed (young and old male and female adults, either volunteers or patients without liver-related diseases). There was a high correlation of the three transferases GOT, GPT and GGT not only with the reported alcohol consumption but also with the plasma insulin. Most of the insulin increase, however, occurred in that range of the three transferases which has been considered to be the normal one. The C-peptide showed the same behaviour. Plasma insulin was also raised in relation to overweight, but only in persons with the sum of the three transferases over 30 U/l, not in persons who did not drink alcohol and who had really normal transferases (sum of the three transferases below 30 U/l measured at 25 degrees C). The quotient of plasma insulin divided by the relative body weight (Broca Index) was constantly low in the range of really normal transferases (up to 30 U/l), thereafter rising significantly, but only in the range of the transferases considered to be the normal one (SGOT to 17, SGPT to 22, GGT to 28 U/l, thus sum up to 67). Serum glucose in the tolerance test also rose with the transferases but much less than the plasma insulin. The correlation between both GGT and the sum of the three transferases with the plasma insulin was significantly positive and independent of the relative body weight. It was concluded that overweight (which is generally believed to be the main risk factor for non-insulin-dependent diabetes), and insulin resistance (which leads to hyperinsulinaemia), are largely caused by the toxic effects of "normal" daily alcohol, more in the human male than in the female.

 Hyperinsulinaemia (which blocks lipolysis) is caused by a toxic effect of ethanol and its metabolites, independent of caloric input and overweight. Hyperinsulinaemia is at least in the human male at present, probably the most important cause of obesity. In obesity, caused by "normal" alcohol consumption, a vicious circle occurs: the enhancement of the triglycerides and, consequently, the free fatty acids leads to a further decrease of glucose utilisation by the muscles which ultimately lead to diabetes.

It is known that chronic alcoholics and type II diabetics show hyperlipidaemia, characterised by hypertriglyceridaemia and in a minor degree by hypercholesterolaemia. The mechanisms underlying the effect of ethanol and carbohydrates on plasma lipids seem to be different; therefore in diabetic subjects, chronic alcohol consumption could produce a more severe hyperlipidaemia and so accelerate atherosclerotic events. In order to verify it Bertello PD et al.⁴⁹ measured plasma cholesterol, HDL-cholesterol, and triglycerides and investigated the presence of micro- and macroangiopathy in two groups of non-insulin-dependent diabetics, differing each other for daily alcohol intake (18 chronic male alcoholics and 30 male subjects consuming respectively more than 150 g and less than 50 g of alcohol daily). In alcoholics, no clinical features, laboratory and echographic findings of cirrhosis and pancreatic disease were present. The data were analysed by Student's "t" and chi-squared tests. No significant differences could be detected (alcoholics/occasional drinkers, means ± 1 SD) either in the plasma levels of cholesterol (181.7 ± 39.3/198.2 ± 32.5), HDL-cholesterol (43.4 ± 12.7/38.5 ± 11.9), and triglycerides (105.5 ± 56.4/159.7 ± 114.8) and in the frequency of micro (22.2%/16.6%) and macroangiopathy (16.6%/26.6%) between the two studied groups.

Snehalatha et al. ²³ performed a study to determine plasma levels of proinsulin (PI) and specific insulin (SI) in normoglycaemic (NGT) Asian Indians and to assess the effect of obesity and impaired glucose tolerance (IGT) on these concentrations. Blood samples from 151 adult non-diabetic South Indian subjects were collected during an epidemiological survey of diabetes. Plasma SI and PI levels were measured in fasting and 30-minute and 120-minute samples of a glucose tolerance test (World Health Organisation criteria) using monospecific antibodies. The total insulin (TI) level was also measured by the non-specific assay. The molar ratio of PI to SI (PI/SI) was calculated. Correlation of the peptides with anthropometry, serum lipids, and blood pressure (BP) were studied by univariate and multivariate analyses. Comparisons were also made in NGT versus IGT groups. As expected, TI values were higher than SI values, but the patterns of response were similar for both. SI and PI responses in NGT were similar to the values found in Mexican-Americans who had a higher body mass index (BMI). Asian Indians were thus found to have a high SI response despite a low BMI. Obesity and IGT produced an increased response of both PI and SI, with normal PI/SI ratios thus showing an absence of hyperproinsulinaemia in either condition. Fasting PI showed a strong association with serum triglycerides, and proinsulin at 120 minutes was associated with cholesterol. None of the peptides showed a correlation with Blood Pressure. Using specific assays for insulin and PI, it was shown that Asian Indians with NGT have a hyperinsulinemic response despite a low BMI. Obesity and mild hyperglycaemia in IGT produce a simultaneous increase in PI and SI with no alteration in the PI/SI ratio.

Considering various studies and data, an expert committee headed by RB Singh⁵⁰ opined that moderate physical activity with the aim of burning 300 Kcal/day (> 1255 KJ/day), and cessation of tobacco and alcohol consumption, may provide an effective programme for prevention of diabetes and its vascular complications in Indians.

 

 

 

 

Material and Methods

Material and Methods

Patients admitted in various medical wards as well as attending Out PatientsÂ’ Department of Mahrana Bhopal General Hospital Udaipur attached to RNT Medical College were included in this study after taking an informed consent.

Four categories of patients were included in this study. Inclusion criteria and exclusion criteria of these group was as below.

Group 1: type 2 diabetics who are alcoholics

Twenty five (25) patients who are

(i) having type 2 diabetes mellitus ,

(ii) aged more than 45 years,

(iii)on glycaemic control with oral hypoglycaemic agents,

(iv) consuming 7 or more drinks per week (moderate to heavy drinkers) for more than five years was included in this group. Exclusion criteria for this group was

(a) any past history of ketosis and

(b) patient requiring insulin for glycaemic control in recent past,

(c) evidence of liver failure or cirrhosis.

 

 

 

Group 2: type 2 diabetics who are ex-alcoholics

Twenty five (25) patients were included in this group. Characteristics of these patients were as following: -

(i)                Age 45 years or more.

(ii)              History of consumption of moderate to heavy amount of alcohol (> 7 drinks per week) for at least 5 years but not consuming alcohol for at least 6 weeks before inclusion in the study.

(iii)            Absence of liver diseases

Group 3: Alcoholics who are non-diabetics

 Twenty five (25) patients with history of intake of moderate to heavy amount of alcohol (7 drinks or more per week) for more than five (5) years with no history or biochemical evidence of diabetes (having fasting and 2-hour post-prandial plasma glucose less than 126 and 200 mg/dl respectively)  was included in this group.

Group 4: Control cohort who are non-diabetics non-alcoholics

Twenty five (25) patients suffering from unrelated illness excluding liver disease with no history of  type 2 or type 1 diabetes mellitus and who had never consumed alcohol was included in this group. All the patients were selected to match other three groups in other demographic characteristics as well.

A detail history was taken to assign patients to corresponding groups. In patients belonging to group 2 and 3, information was gathered regarding onset and progress of diabetic symptoms and duration of diabetes. 

Particular emphasis was given on history of addiction especially alcohol intake. PatientÂ’s drinking patterns was ascertained by questionnaire and was crosschecked with relatives where available. A rough estimate of weekly alcohol consumption was made. History of other addictions, especially smoking, was also taken.

A detail drug history assessing intake of various anti-diabetic and other medications was made to ascertain any confounding factors while comparing alcohol drinker with non-alcohol drinker groups. Compliance was assessed by questioning patient and relatives.

A complete physical examination was done to find out any clinical evidence of microangiopathic along with macroangiopathic complications of type 2 diabetes mellitus. Height was measured in centimetres against a calibrated wall in standing erect posture. Weight was measured using a standard spring balance. Body Mass Index (BMI) was calculated from these measurements. Waist girth was measured as the minimum circumference between iliac crest and rib cage, and hip girth was measured at the maximum width over the greater trochanters. Waist-Hip ratio (WHR) was calculated from these measurements. Blood Pressure was measured using a standard mercury manometer in sitting posture after rest for 5 minutes. An high BP was confirmed by two more measurements

 Care was taken to detect evidence of hepatic dysfunction and those cases was excluded from study.

Patients were then investigated. Routine examinations included fasting and post-prandial plasma glucose, serum urea and creatinine, urine for albumin, sugar, ketone and microscopy. Other routine investigations included billirubun, SGOT, SGPT and Ultrasonography of abdomen for evaluation of hepatic function.

Plasma glucose was estimated by enzymatic method called GOD/POD METHOD⁵². Principle of this test is as below

Glucose is oxidised by the enzyme Glucose oxidase (GOD) to give D-Gluconic acid and hydrogen peroxide. Hydrogen peroxide in presence of enzyme peroxidase (POD) oxidises phenol which combines with 4-aminoantipyrine to produce a red coloured quinoneimine dye. The intensity of colour produced is proportional to the glucose concentration of the sample.

Method: Clean, dry test tubes were labelled as Blank (B), Standard (S) and Test (T). In each of the tubes, 1.0 ml of prepared working enzyme were added. To the test tube labelled B, S and T, respectively 10 µl of distilled water, 10 µl of standard solution (containing 100 mg/dl glucose concentration) and 10 µl of test serum were added. They were mixed well and incubated at 37° C for 15 minutes. Then the adsorbance of the test (T) and Standard (S) were measured against blank on a photocolorimeter with a green filter at 505 nm.

Glucose in mg/dl = A of (T) /A of (S) x 100

Cholesterol and Triglycerides were measured by standard enzymatic methods as described below using Stat Fax® semi-autoanalyser.

LIPID PROFILE ESTIMATION BY SEMI AUTOANALYZER[STAT FAX 2000]

1. TOTAL CHOLESTEROL (Enzymatic method) ⁵³

PRINCIPLE: -                      Cholesterol

                                              Esterase

     Cholesterol Ester + H₂O ¾¾¾¾® Cholesterol + Fatty acids

                                  Cholesterol

                                  Oxidase

     Cholesterol + O₂ ¾¾¾¾® Cholestenone + H₂O₂

                                                                  Peroxidase

     2H₂O₂ + Phenol + 4-Aminoantipyrine ¾¾¾® Red quinone + 4 - H₂O₂

The concentration of cholesterol in the sample is directly proportional to the intensity of the red complex (Red Quinone) which is measured at 500 nm.

2. TRIGLYCERIDES ^{54, 55}

          PRINCIPLE: -         

                                           Lipase 

       Triglycerides  + H₂O ¾¾¾¾® Glycerol + Free Fatty acids.

                                         GK 

 Glycerol + ATP ¾¾¾¾® Glycerol - 3- phosphate + ADP.

                                                      

                                                                                                                                                                                                                                                                                                                                                  GPO   

Glycerol - 3- phosphate + O₂ ¾¾¾¾® DAP + H₂O₂.

                                      

                                             Peroxidase

H₂O₂ + 4 AAP + DHBS ¾¾¾¾® Quinoneimine dye + 2 H₂O

GK        =    Glycerol Kinaes

GPO      =    Glycerol Phosphate Oxidase

DAP      =    Dihydroxyacetone phosphate

ATP      =    Adenosine triphosphate

4- AAP =     4 Aminoantipyrine

DHBS   =     3,5- dicholoro-2-hydroxybenzene sulfonate

H2O2     =     Hydrogen Peroxide

 

The absorbance of standard and each sample tube were read against reagent blank at 510 nm.

Among the special investigations, fasting insulin levels was determined by Radioimmunoassay (RIA) method using I¹²⁵ tracer bound antibodies in an approved laboratory. RIA is a structurally specific immunochemical assay which measures Immunoreactive Insulin. It is an extraordinary sensitive and specific which can measure concentration as low as 10^-13 mole of substance. ⁵⁷

Sample collection and preparation: Serum or plasma was used and the usual precautions for venipuncture were observed. Specimens were stored at 2 to 8°C for up to 24 hours or frozen at ­20°C or lower for longer periods.

Principles of the test:^56,58 The procedure follows the basic principle of Radioimmunoassay where there is a competition between a radioactive and a non-radioactive antigen for a fixed number of antibody binding sites. The amount of I¹²⁵ labeled insulin bound to the antibody is inversely proportional to the concentration of unlabeled insulin present. The separation of free and bound antigen is easily and rapidly achieved by using a double antibody system.

Assay Procedure: The assay was done using the DSL-1600 Insulin RIA kit manufactured by the Diagnostic Systems Laboratories, Inc., Webstar, Texas, USA.

1.             All the assay reagents were allowed to reach room temperature (~25°C) after removing from the refrigerator and mixed before use by gentle and thorough shaking. After reconstitution of Standards and Controls, they were mixed thoroughly, avoiding foam.

2.             Plastic tubes (12x75mm) were labeled and arranged for Total counts, Standards, Controls, Non-specific binding (NSB) and samples were studied in duplicate.

3. To the appropriate tubes 100 µl of the Insulin Standards, Controls, and serum samples of the corresponding study subjects were added. In NSB tubes 200 µl of the 0 µIU/ml Insulin Standard were added.

4. In all tubes, except NSB and Total count tubes 100µl of Insulin Antiserum were added.

5. 100µl of Insulin I¹²⁵ reagent were added to each tube.

6. All tubes were vortexed.

7. Tubes were incubated at 2-8°C for 16 hours.

8. To all tubes except Total Count tubes 1 ml of precipitating reagents were added after being shaken thoroughly.

9.  All tubes were vortexed.

10. Tubes were incubated at room temperature (~25ºC) for 10 to 15 minutes.

11. All tubes, except Total count tubes, were centrifuged at 1500 ´ g for 20 minutes.

12. All tubes, except the Total count tubes, were decanted by simultaneous inversion with a sponge receptacle. They were allowed to be drained on absorbent material for 15-30 seconds and were gently blotted to remove any droplets adhering to the rim before returning them to the upright position.

 

13. All the tubes were counted in a gamma counter for one minute.

14. Mean counts per minute (cpm) were calculated for each Standard, Control and unknown serum samples. Mean counts per minute for non-specific bindings were subtracted from all counts to obtain corrected results. For each Standard, Control and test serum sample % B/B₀ was calculated as

% B/B0 =	Mean Sample counts - NSB counts	X 100
	Mean cpm of zero Insulin Standards - NSB counts

 

15. A curve of % B/B₀ for each Standard against the insulin concentration was plotted on a semi-log graph paper. A standard curve was drawn through the means of duplicate points. From this standard curve, concentrations of test and control sample were determined

After measuring serum Insulin, Quantitative insulin sensitivity check index and HOMA indices was calculated from the formula

QUICKI= 1/ [log₁₀ (Insulin₀) + log₁₀ (Glucose₀)]

HOMA-IR ={Insulin₀ X(Glucose₀/18)}/22.5

HOMA‑BCF= (20XInsulin₀) / {(Glucose₀/18) – 3.5} where Insulin₀ fasting insulin in µu/ml and Glucose₀ is fasting glucose in mg/dl

After collection of data they were tabulated. Statistical analysis was done including t-test for comparison among all four above mentioned groups. Various confounding variables were matched. Assessment of surrogate markers of insulin resistance such as Body Mass Index (BMI), Waist-Hip ratio (WHR) and Serum Triglyceride were done by comparing with the measured value of Insulin Sensitivity Index.

By comparing all four groups amongst themselves by t-test, effect of alcohol consumption on insulin resistance in diabetics as well as non-diabetics was ascertained. Correlation between various parameters was determined by PearsonÂ’s univariate regression analysis and multivariate regression analysis.

 

 

 

 

 

Observations

Observations

In this study, patients admitted in various wards and attending the OPD of Maharana Bhupal Government Hospital were included. Clinical examination, anthropometric measurements and bio-chemical assay was conducted in patients belonging to each of four mutually exclusive groups, Group A: Type 2 diabetic alcoholics. Group B: Type 2 diabetic ex-alcoholic, Group C: Non-diabetic alcoholic and Group D: Non-diabetic non-alcoholic control. Following observations were obtained from the study.

Table 1: Comparison of clinical parameters among groups

* NA not applicable, significant p values are marked in bold letters.

The table above depicts comparison of clinical and anthropometric characteristics of the study groups. It is seen that the non-diabetic alcoholic group (Group C) were younger than other groups. They also had a significantly lower Body Mass Index (BMI), Waist circumference and Waist-Hip Ratio (WHR). The diabetics who were continuing to imbibe alcohol (Group A) had a shorter duration of diabetes (37.8 ± 64.4 months) compared to ex-alcoholic diabetics (Group B), who had a mean duration of 83.9 ± 123.8 months, but the difference did not reach statistical significance. As expected, alcoholics had higher exposure to smoking but this was not a statistically significant confounding factor. Patients belonging to group B had a significantly higher systolic blood pressure [136.7 ± 21.2 compared to 122.6 ± 21.6, p value =0.01] compared to the control group (Group D) as well as a higher WHR.

 

Table 2: Comparison of biochemical parameters in study groups

* significant p values are marked in bold letters

This table compares the biochemical parameters in the four study groups. Though the diabetics had a significantly higher fasting as well as post‑prandial plasma glucose level than the non diabetics, there was no significant difference in plasma glucose levels of the two non-diabetic groups. All the four groups had similar urea, creatinine and aminotransferase levels indicating difference in renal or hepatic function did not confound the comparison of results. It is also seen that diabetes was associated with significant hypertriglyceridemia as well as hypercholesterolemia but alcohol intake in non-diabetics was not associated with lipid abnormality.

 

Table 3: Comparison of various measures of insulin sensitivity/resistance and beta cell function among study group

 

 

The table above compares fasting insulin, Quantative Insulin Sensitivity Check Index [QUICKI], Insulin Resistance by Homeostasis Model assessment [HOMA-IR], and β-cell function as percentage normal calculated by Homeostasis model assessment [HOMA-BCF] amongst the study groups. We  found that QUICKI was lower in diabetics who continued to take alcohol (Group A) and they had a higher serum insulin level comparable to diabeic ex‑alcoholics (Group B). The mean  insulin resistance (HOMA-IR) in Group A was 23.2 ± 56.3, which was higher than that of Group B and Group C (  14.1 ± 15.6 and 4.7 ± 3.3) but he difference did not attain statistical significance due to excessive variance in the former group. HOMA-BCF was comparable in all 4 groups.

 

Table 4: Correlation between Insulin Resitance and clinical parameters

 r = Correlation co-efficient, n= number of subjects,

The table above shows correlation between various clinical parameters and measures of insulin sensitivity and resistance as determined by univariate regression analysis. Though QUICKI was inversely correlated to age, HOMA-IR did not show such correlation. In alcoholics, there was significant correlation of QUICKI and HOMA-IR with duration of alcohol intake  but not with amount of alcohol consumed. In diabetics who have given up alcohol, insulin sensitivity (as measured by QUICKI) directly correlated with period of discontinuation of alcohol.

Height, weight and BMI did not predict insulin resistance. On the other hand,  higher waist circumference and Waist-Hip Ratio was associated with insulin resistance. Neither systolic nor diastolic blood pressure had significant correlation with measure of insulin sensitivity.

Figure1: Correlation between WHR and QUICKI

The figure above shows regression curves of Waist-Hip Ratio and QUICKI in the four groups of patients in the study. It is seen that QUICKI steadily decreases with rise of WHR. The correlation is more significant in non‑diabetics (Groups C and D) as evident by steeper curve in those groups.

Figure 2: Correlation between QUICKI and duration of alcohol intake

 

 

This figure shows regression curves of relation between duration of diabetes with insulin sensitivity (QUICKI). There is definite fall in QUICKI values indicating decline in insulin sensitivity in diabetics with longer duration of alcohol intake. The change was most prominent in Group A, diabetics who continued to drink (r² =0.171, p=0.02). But in non-diabetic alcoholics (Group C), there was no correlation between duration of alcohol intake and QUICKI (r² = 0.034, p not significant).

 

 

 

 

 

Figure 3: Correlation between amount of alcohol intake and insulin resistance

 

The figure above depicts the relationship between amount of alcohol consumption per week and insulin resistance measured by HOMA model. Due to wide range of HOMA-IR values a logarithmic scale was taken. There was no significant effect of amount of alcohol consumed on insulin resistance, both in diabetics and the non-diabetic alcoholic group although there was a downward trend, which was non-significant statistically.

Figure 4: Effect of discontinuation of alcohol intake in diabetics

 

The figure above illustrates the effect of discontinuation of alcohol in diabetics. There is an upward trend in insulin sensitivity as measured by QUICKI with longer period of abstinence from alcohol (r² =0.218, p<0.01).   HOMA-IR did not show any significant correlation

 

 

 

 

 

 

 

 

 

 

 

 

Table 5: Correlation between Insulin Resistance and Biochemical parameters

 

The table above shows the relation between biochemical marker and insulin resistance. We can see that both fasting and post-prandial plasma glucose levels highly correlated with insulin resistance (p< 0.001). Among the aminotranferases, alanine aminotransferase (SGPT) was directly correlated to insulin resitance but aspartate aminotransferase (SGOT) did not show such correlation. Hypercholesterolaemia and hypertriglyceridemia are associated with rise in HOMA-IR and fall in QUICKI suggesting that they are good marker for insulin resistance.

 

Table 6: Comparison of various indices related to insulin resistance in non‑diabetics according to amount of alcohol intake

 

Amount of weekly alcohol consumption (g/wk)		Insulin		QUICKI		HOMA‑IR		HOMA‑BCF
	n	Mean	SD	Mean	SD	Mean	SD	Mean	SD
0	25	17.9	8.9	0.329	0.033	3.5	2.0	1528	2760
1-500	8	30.9	21.9	0.307	0.034	6.0	4.1	1027	782
501-1000	9	20.8	12.6	0.321	0.041	4.5	2.8	1419	2427
1001-1500	5	16.8	10.6	0.331	0.052	4.0	2.9	462	448
>1500	2	8.7	0.14	0.347	0.012	1.9	0.5	180	153

 

As shown in the table above, non‑alcoholics had a lower insulin level of 17.9 ± 8.9 µu/ml compared to persons consuming up to 500 gm and 500 to 1000 gm of ethyl alcohol per week (insulin levels 30.9 ± 21.9 µu/ml and 20.8 ± 12.6 µu/ml, respectively). On the other hand, persons consuming 1000 gm or more alcohol per week were having insulin level lower than non-alcoholic population. This fall in insulin level was associated with a rise in QUICKI and fall in HOMA-IR. An interesting observation obtained is that persons consuming a heavy amount of alcohol were having β‑cell function (as determined by HOMA equation) below that of normal persons.

However after adjusting for age, BMI and WHR by doing a multivariate regression analysis, the correlation between amount of alcohol consumed and insulin sensitivity becomes non‑significant statistically(t=0.20, p=NS).

 

 

 

 

 

Discussion

Discussion

The incidence of type 2 diabetes and its complications has reached an alarming proportion in recent years. With the projected further rise in the disease worldwide, particularly in India, it has become necessary to elucidate factors which affect and modify the aetiopathogenesis of the disease, namely insulin resistance and β‑cell dysfunction. Proper delineation of effects of various dietary and lifestyle factors on progression of diabetes will not only lead to better patient care in form of proper advice based on evidence, but also help in forming a strategy in the primordial prevention of the disease and its risk factors in community.

There has been a significant rise of alcohol consumption due to increased urbanisation and easy availability of alcohol in India in recent times. Quite a few studies have been done in Western as well as Far Eastern nations which evaluated effect of regular alcohol consumption on insulin levels and progression of diabetes both in diabetics ^21,42,43 and non‑diabetics ^20,22,46,47. Hence this study was planned to assess the effect of regular alcohol intake in a small population sample of patients attending RNT Medical College and Hospitals consisting of both diabetics and non-diabetics who differ in their alcohol intake. We found no study which reported the effect of alcohol in subjects of Indian sub-continent. As this population group vary considerably, as per the risk factors of diabetes is concerned, from occidental populace^13,14 and most of the  subjects here consume country liquor of questionable quality¹⁹, the effect may be different from what was obtained in Western literature.

A total of one hundred subjects were included in this study with twenty five patients in each of the following groups: Group A- type 2 diabetic alcoholics; Group B – type 2 diabetic ex-alcoholics; Group C- non‑diabetic alcoholics; and Group D- non-diabetic non-alcoholics.  The mean (± SD) ages of the four groups were 51.7 ± 10.2, 50.4 ± 10.8, 46.8 ± 8.2 and 54.9 ± 13.9 years, indicating that non‑diabetic alcoholics were younger. This is due to random enrolment in the study and age standardisation was done by multivariate regression analysis.

Though smoking was more commonly associated with alcohol intake, the difference was not significant enough to confound the results.

On comparing the study groups, we found that diabetics had higher Body Mass Index (BMI), Waist Circumference and Waist‑Hip Ratio (WHR) index. These findings are in consonance with that of various previous investigators who found that anthropometric measurements are often high in diabetics or persons with impaired glucose tolerance^29,31. Non‑diabetics who are alcoholics (Group C) had a still lower WHR than non‑diabetic non‑alcoholics. This may be due to (i) their lower age or (ii) poor nutritional intake associated with alcoholism.

Ex-alcoholic diabetics had a significantly higher systolic blood pressure compared to non-alcoholic non-diabetic controls. The frequent co-existence of hypertension and diabetes has been reported in epidemiological studies and is explained by presence of hyperinsulinaemia in these conditions^12,59.

Diabetics were having significantly elevated plasma glucose levels compared to non‑diabetics. Though there was no difference in fasting glucose levels, the post-prandial levels were higher in alcoholics than ex-alcoholics. Though acute alcohol is known to cause hypoglycemia in normal persons by inhibiting gluconeogenesis, similar effect has not been observed in diabetics³⁸. However it will be premature to comment on effect of ethanol on long-term glycaemic control based on plasma glucose levels alone in absence of data about glycosylated haemoglobin levels.   Even in non-diabetics, regular alcohol consumption did not cause significant effect on plasma glucose level compared to non-alcoholics, which is comparable to result obtained in the prospective study by Davies MJ et al. ⁴⁷. In the long term prospective studies like Osaka study²⁰, alcoholics are found to be having less chance of developing diabetes unless they are lean.

Serum cholesterol and triglyceride levels were significantly higher in diabetic population. This may be due to higher level of serum insulin in them. The association between hyperinsulinaemia and hypercholesterolaemia/ hypertriglyceridaemia has also been previously documented in CARDIA Study³².  However, no significant difference was obtained in cholesterol and triglyceride levels of diabetics differing on alcohol intake (Group A and B). This finding is in similar to that obtained by Bertello et al. ⁴⁹. Moreover non-diabetic alcoholics and non‑diabetic non‑alcoholics did not differ significantly in their cholesterol and triglyceride levels. This observations was similar to that of ‘Bruneck StudyÂ’²² but differs from that obtained by Davies et al. in their prospective study ⁴⁷.

The hepatic enzymes [SGOT(AST) and SGPT(ALT)] did not differ in alcoholics and non-alcoholics. On the other hand Kornhuber H et al ⁴⁸ found that elevated levels of these enzymes are associated with alcohol induced liver damage. The difference may be due to differences in assay procedure or confounding presence of other hepatotoxic element in non‑alcoholic subjects of our study.

Various studies previously used different measures of insulin sensitivity in measuring the effects alcohol, thereby their direct comparison is not possible. In our study we had selected four well-established measures of insulin sensitivity and resistance, namely fasting insulin (FI), Quantitative Insulin Sensitivity Check Index (QUICKI), Insulin Resistance by Homeostasis Model Assessment (HOMA-IR) and β-cell function by HOMA (HOMA-BCF). We found that diabetics had a significantly higher serum insulin and HOMA-IR and lower QUICKI values compared to non-diabetics. The difference became more significant in QUICKI values due to its less variability. However alcohol consumption did not cause significant alteration of the parameters in non-diabetics. The fact that HOMA‑BCF was similar in all four groups probably indicate that the pancreatic β -cells are probably not directly affected by alcohol consumption.

While correlating various clinical parameters by univariate analysis, we found that QUICKI is significantly and inversely correlated with duration of alcohol intake, indicating prolonged alcohol intake decreases insulin sensitivity. On subgroup analysis, the fall of insulin sensitivity was most prominent in diabetic alcoholic group, whereas in non-diabetic alcoholic the correlation was statistically non-significant. This indicates that deleterious effects of alcohol in diabetics increase with prolonged exposure.

Amount of alcohol intake did not have any statistically significant effect on insulin sensitivity though a downward trend in HOMA-IR was obtained with increasing alcohol consumption. Previous studies^{20, 22, 46} have shown a significant fall in insulin concentration as well as insulin resistance with moderate amount of alcohol consumption. The difference may be due to inherent folly of the questionnaire method adopted in determining alcohol consumption in this study, difference in the quality of alcohol consumed and its contaminants or due to different genetic susceptibility of our study population. Furthermore, there was a downward trend, albeit non‑significant, in insulin resistance with increasing amount of alcohol consumption in all three groups. When only non‑diabetic subgroups were studied, it was found that insulin level, insulin resistance and β‑cell function falls and QUICKI values rise with increasing amount of alcohol consumption. This finding was also obtained by previous investigators. However, these relations became non-significant when other variables like age, BMI, WHR were matched by multivariate regression analysis making us to echo the observation of Bell et al ⁴⁴that improved insulin sensitivity associated with moderate alcohol consumption might be a function solely of a more favourable adiposity profile. However, the factual history, as per as exact amount of spirit consumed by an individual, is very difficult to assess on account of an inherent personality profile of a person consuming alcohol for a long time. All previous study such as ours have been population based but they point in a direction which should be worked upon using as many subjects as possible who are quantitatively documented to be consuming alcohol such as bar-workers, people visiting pubs.

In the patients included in our study, insulin sensitivity was inversely related to Waist Hip Ratio whereas it was not related at all to BMI. This peculiar situation is specifically described^7,60 in Asian Indians who have a higher WHR despite having a low BMI associated with insulin resistance.

Surprisingly, markers of insulin resistance were not correlated with systolic and diastolic blood pressure in the study subjects. In there population based study in New Zealand, McAuley et al ⁶¹ also did not found any correlation between Insulin sensitivity determined by Insulin Clamp and hypertension. On the other hand, taking fasting and postprandial insulin levels as markers for insulin resistance, Kothari K et al ⁶² found increased insulin levels in hypertensives. The cross‑sectional nature of the study is inadequate to delineate the complex relationship between insulin resistance syndrome and hypertension.

Among the biochemical parameters, blood glucose (fasting and post‑prandial), SGPT, total cholesterol and triglyceride were inversely related to QUICKI and directly related to HOMA-IR. Various previous studies^63,64 have also confirmed usefulness of these markers of insulin resistance.

When the effect of discontinuation of alcohol on insulin sensitivity was evaluated in the diabetic ex-alcoholic group, it was found that there is a rising trend in QUICKI with prolonged period of abstinence. This correlation persisted even after adjusting for age, anthropometric parameters and amount of alcohol consumed. This may indeed indicate the beneficial effect of stoppage of alcohol consumption on improving insulin sensitivity. A prospective long-term study is warranted to explore this association.

 

An attempt has been made through this pilot study to find out a possible relation between alcohol consumption and diabetes in India as both diabetes and alcohol consumption are on the rise. Although clear-cut scientific inference ccould not be drawn by this small study on such a sensitive matter unless a larger study carried on faithful alcoholics, where exact alcohol consumption can be quantified, is performed, this study is a pointer to the fact that chronic alcohol consumption in so called moderate amount does lead to lead to insulin resistance and glucose intolerance. Much has been commented upon the effects of abnormal waist-hip ration on glucose metabolism. Chronic alcohol consumption in many patients has cased truncal obesity with increased WHR. In our opinion this observation is significant in Indian context, whereas sporadic reports from the West indicated that moderate alcohol consumption in not harmful in diabetics. In our situation, where alcohol produced is of inferior quality along with other nutritional drawbacks, alcohol consumption should be discouraged.

 

 

 

 

 

Summary and Conclusions

Summary and Conclusions

This study was conducted in admitted and out‑patients of Maharana Bhupal Government Hospital. The possible effects of prolonged consumption of ethyl alcohol on insulin resistance on diabetic and non‑diabetic individuals were determined by measuring various clinical and biochemical markers and calculating various indices of insulin resistance in four groups of twenty five subjects each: (A) diabetic alcoholics, (B) diabetic ex‑alcoholics, (C) non‑diabetic alcoholics and (D) non-diabetic non‑alcoholics. The following conclusions could be drawn from this study: -

a.      Diabetic subjects (groups A and B) in this study in general had higher Waist-Hip Ratio (WHR), plasma glucose, total cholesterol, triglyceride and serum insulin levels than the non‑diabetic subjects (groups C and D).

b.     Alcohol consumption did not significantly alter anthropometric variables, blood pressure, glycaemia, liver enzymes or triglyceride and cholesterol levels in both diabetics and non‑diabetics.

c.      Quantitative insulin sensitivity check index (QUICKI) was inversely and Insulin resistance by Homeostasis Model Assessment (HOMA-IR) was directly correlated with Waist-Hip Ratio, fasting and post-prandial plasma glucose, Alanine Amiinotransferase (SGPT), serum fasting cholesterol and triglyceride but not related to Body Mass Index or blood pressure.

d.     Though diabetic alcoholics had higher fasting insulin and HOMA‑IR indices than diabetic ex‑alcoholics, the difference was not significant statistically.

e.      In diabetics insulin sensitivity decreased with increasing duration of diabetes but tended to be lower with higher consumption of alcohol.

f.       In diabetic ex‑alcoholics insulin sensitivity improved proportionate to the period of stopping alcohol.

g.      In non-diabetics, increased alcohol consumption was associated with improved insulin sensitivity but this appeared due to favourable effect of alcohol on body composition, namely lower WHR and BMI.

This study presented an overview of literature regarding effect of alcohol consumption in determining insulin resistance, both in diabetics and non‑diabetics. In view of the conflicting effects obtained in various studies, a prospective longitudinal study is required to ascertain complex metabolic effects of ethyl alcohol on insulin resistance.

 

 

 

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Miscellaneous

 

Relationship between Alcohol Consumption and Insulin Resistance

PROFORMA FOR STUDY

 

Case No#

·        Name______________________ Age _________ years                                          

·        Address_________________________

·        Reg No. _______________          Ward/Bed No. ________/OPD

Classification of case

1.      Group 1: Normal Subject                                                                          []

2.      Group 2: Type 2 elderly diabetic consuming moderate alcohol                 []

3.      Group 3: Type 2 diabetic who has given up alcohol                                  []

4.      Group 4: Alcoholic who is non-Diabetic                                                   []

 

history of diabetes (Group 2 and 3)

1.       Diagnosed diabetic _____years _________months back at ____ years of age

2.       Symptoms at presentation

a)      Asymptomatic/ Incidental diagnosis

b)      Polyphagia

c)      Polyuria

d)      Polydipsia

e)      Weakness

f)       Tingling /numbness

g)      Infections/Abscess

h)    Others (description)  _______________________________

3.      History of Complications (if any)

history of addiction

1.       No addiction               Yes []                           No []

2.      Alcohol                                    Yes []                           No []                           

a)      Duration of intake ______________years

b)      Average weekly consumption = _______ ml of ____________liquor containing approximately ____% of alcohol = _____ g of Alcohol

c)      Sweetened []                                  Non-sweetened

d)      Social drinker/ Addict

e)      Stopped drinking _____year ____months back

3.      Smoking                                  Yes []                           No []

a)      Duration of smoking ________years

b)      No of Average bidis/ cigarettes per day __________

c)      Total exposure _______ pack-years (1 pack = 20 cigerettes/bidis)

d)      Stopped smoking _____years _____months back

4.      Chewing tobacoo                     Yes []                           No []

a)      Duration _____________years

5.      Others _________________________________________

 

 

family history

History of	Diabetes type 2	Diabetes type 1	CVA	Hypertension	CAD
Father
Mother
Brother(s)
Sister(s)
Other(s)

 

medication history

1.       Insulin                         Yes []                           No []

a)      Average daily dose _________ IU

b)      Type                      Regular            Lispro              NPH                Lente  

c)      Started _____year _____month ago ______ months after diagnosis of DM

2.      Suphonylureas             Yes []                           No []

a)      Drug used (Generic) ______________

b)      Dose ______mg/day ~  ____% of maximum recommended dose      [glibenclamide 20 mg, glimepiride 8 mg, glipizide 40mg, gliclazide 160mg]

c)       Started _____year _____month ago _____ months after diagnosis of DM

3.      Meglitinide(Repaglinide)         Yes []                           No []

a)      Dose _______mg/d

b)      Started _____year _____month ago ______ months after diagnosis of DM

4.      Biguanide (Metformin)            Yes []                           No []

a)      Dose  ________mg/d

b)      Started _____year _____month ago ______ months after diagnosis of DM

5.      Acarbose                                 Yes []                           No []

6.      Thiozolidinediones      Yes []                           No []

a)      Drug _________________ dose ________mg/d

b)      Started _____year _____month ago ______ months after diagnosis of DM

7.      Others

a)      β-blockers                         Yes []                           No []

b)      ACE inhibitors      Yes []                           No []

c)      Diuretics                Yes []                           No []

d)      Aspirin                   Yes []                           No []

e)      Others

 

Assessment of Compliance      Good []            Moderate []      Poor []

 

physical examinationation

 

Height	cm	Weight	Kg	BMI
Waist Circ.	cm	Hip Circ.	cm	WHR
Pulse	/min	SBP	mm Hg	DBP	mm HG

 

Findings                                                                                                                                                                                                                                                                                                           Present                                                                                                                                                             Absent

§         Cataract                                                     []                                   []                                     

§         Retinopathy                                               []                                    []                                     

§         Skin changes                                              []                                    []

§         Xanthoma                                                  []                                    []

§         Edema                                                       []                                    []

§         Neuropathy                                               []                                    []

§         Diabetic foot                                             []                                    []

§         Nephropathy                                             []                                    []

 

investigations

TEST	VALUE	NORMAL VALUE
Venous Plasma Glucose (fasting)	mg/dl	<126 mg/dl
Venous Plasma Glucose (2hr Postprandia)	mg/dl	<200 mg/dl
Serum Urea	mg/dl	15-40 mg/dl
Serum Creatinine	mg/dl	0.7-1.5 mg/dl
Urine Sugar		Nil
Urine Albumin		Nil
Urine Ketone		Nil
Urine Microscopy
SGOT	IU/L	5-25 IU/L
SGPT	IU/L	5-25 IU/L
SPECIAL INVESTIGATIONS
Serum Insulin (Fasting)	mU/ml	5-25 mU/ml
Total Cholesterol(Fasting)	mg/dl	<200 mg/dl
Triglyceride(Fasting)	mg/dl	< 150 mg/dl
USG Abdomen For liver and Portal vein

 

 

 

 

 

 

 

Consent Form

I consent for inclusion in this study voluntarily and collection of blood sample and personal data for the same.

 

 

 

 

Signature of Patient

अनुमति पत्र

मैं किये जा रहे शोध के लिये व्यक्तिगत जानकारी व खुन कि जाँच की अनुमति देता हुँ

 

हस्ताक्षर  रोगी