Index

1.Introduction

2.Literature review

3.Noteworthy contribution

4.Globe challenge and opportunity

5.Future prospects

6.Conclusion

7.Reference

1

INTRODUCTION

2

INTRODUCTION

Obesity

Obesity is a medical condition in which excess body fat has accumulated to the extent that it

may have an adverse effect on health, leading to reduced life expectancy and/or increased health

problems.[1][2] Body mass index (BMI), a measurement which compares weight and height,

defines people as overweight (pre-obese) if their BMI is between 25 and 30 kg/m2, and obese

when it is greater than 30 kg/m2.[3]

Obesity increases the likelihood of various diseases, particularly heart disease, type 2 diabetes,

obstructive sleep apnea, certain types of cancer, and osteoarthritis.[2] Obesity is most commonly

caused by a combination of excessive food energy intake, lack of physical activity, and genetic

susceptibility, although a few cases are caused primarily by genes, endocrine disorders,

medications or psychiatric illness. Evidence to support the view that some obese people eat little

yet gain weight due to a slow metabolism is limited; on average obese people have a greater

energy expenditure than their thin counterparts due to the energy required to maintain an

increased body mass.[4][5]

Obesity

Classification and external resources

Fig: Silhouettes and waist circumferences representing normal, overweight, and obese

3

Dieting and physical exercise are the mainstays of treatment for obesity. Moreover, it is

important to improve diet quality by reducing the consumption of energy-dense foods such as

those high in fat and sugars, and by increasing the intake of dietary fiber. To supplement this, or

in case of failure, anti-obesity drugs may be taken to reduce appetite or inhibit fat absorption. In

severe cases, surgery is performed or an intragastric balloon is placed to reduce stomach volume

and/or bowel length, leading to earlier satiation and reduced ability to absorb nutrients from

food.[6][7]

Obesity is a leading preventable cause of death worldwide, with increasing prevalence in adults

and children, and authorities view it as one of the most serious public health problems of the

21st century.[8] Obesity is stigmatized in much of the modern world (particularly in the Western

world), though it was widely perceived as a symbol of wealth and fertility at other times in

history, and still is in some parts of the world.[2][9]

CLASSIFICATION OF OBESITY

Obesity is a medical condition in which excess body fat has accumulated to the extent that it may

have an adverse effect on health.[1] Relative weight and body mass index (BMI) are nearly

identical and are reasonable estimates of body fatness as measured by percentage body fat.[2]

However, BMI does not account for the wide variation in body fat distribution, and may not

correspond to the same degree of fatness or associated health risk in different individuals and

populations.[3][4][5] Other measurements of fat distribution include the waist–hip ratio and body fat

percentage. Normal weight obesity is a condition of having normal body weight, but high body

fat percentages with the same health risks of obesity.[6][7]

BMI

Body mass index or BMI is a simple and widely used method for estimating body fat mass. [8]

BMI was developed in the 19th century by the Belgian statistician and anthropometrist Adolphe

Quetelet.[9] BMI is an accurate reflection of body fat percentage in the majority of the adult

population. It however is less accurate in people such as body builders and pregnant women.[10] A

formula combining BMI, age and gender can be used to estimate a person's body fat percentage

4

to an accuracy of 4%.[11] An alternative method, body volume index (BVI), is being developed in

an effort to better take into account different body shapes.[12]

BMI Classification

< 18.5 underweight

18.5–24.9 normal weight

25.0–29.9 overweight

30.0–34.9 class I obesity

35.0–39.9 class II obesity

≥ 40.0   class III obesity  

BMI is calculated by dividing the subject's mass by the square of his or her height, typically

expressed either in metric or US "Customary" units:

Metric: BMI = kilograms / meters2

US/Customary and imperial: BMI = lbx703 / in2

where lb is the subject's weight in pounds and in is the subject's height in inches.

The most commonly used definitions, established by the World Health Organization (WHO) in

1997 and published in 2000, provide the values listed in the table at right.[13]

Some modifications to the WHO definitions have been made by particular bodies. The surgical

literature breaks down class III obesity into further categories, though the exact values are still

disputed.[14]

Any BMI ≥ 35 or 40 is severe obesity

A BMI of ≥ 35 or 40–44.9 or 49.9 is morbid obesity

A BMI of ≥ 45 or 50 is super obese

5

As Asian populations develop negative health consequences at a lower BMI than Caucasians,

some nations have redefined obesity. The Japanese have defined obesity as any BMI greater than

25[15] while China uses a BMI of greater than 28.[16]

Waist circumference and waist–hip ratio

In the United States a waist circumference of >102 cm in men and >88 cm in women[17] or the

waist–hip ratio (the circumference of the waist divided by that of the hips of >0.9 for men and

>0.85 for women) are used to define central obesity.[18]

In the European Union waist circumference of ≥ 94 cm in men and ≥ 80 cm in non pregnant

women are used as cut offs for central obesity.[19]

A lower cut off of 90 cm has been recommended for South Asian and Chinese men, while a cut

off of 85 cm has been recommended for Japanese men.[19]

In those with a BMI under 35, intra-abdominal body fat is related to negative health outcomes

independent of total body fat.[20] Intra-abdominal or visceral fat has a particularly strong

correlation with cardiovascular disease.[18] In a study of 15,000 people, waist circumference also

correlated better with metabolic syndrome than BMI.[21] Women with abdominal obesity have a

cardiovascular risk similar to that of men.[22] In people with a BMI over 35, measurement of

waist circumference however adds little to the predictive power of BMI as most individuals with

this BMI have an abnormal waist circumferences.[23]

Body fat percentage

Cross-sections of the torso of a person of normal weight (left) and an obese person (right), taken

by CT scan. Note the 3.6 cm (1.4 inches) of subcutaneous fat on the obese person.

6

Body fat percentage is total body fat expressed as a percentage of total body weight. There is no

generally accepted definition of obesity based on total body fat. Most researchers have used

>25% in men, and >30% in women, as cut-points to define obesity. [24] However, the finding that

metabolic disturbance increases with increasing body fat percentage[25] suggests that focusing

exclusively on cut-points of body fat percent may be of limited value.

Body fat percentage can be estimated from a person's BMI by the following formula:

Bodyfat% = (1.2 * BMI) + (0.23 * age) − 5.4 − (10.8 * gender)

where gender is 0 if female and 1 if male

This formula takes into account the fact that body fat percentage tends to be 10 percentage points

greater in women than in men for a given BMI. It recognizes that a person's percentage body fat

tends to increase as they age, even if their weight and BMI remain constant. The results of this

formula have been shown to have an accuracy of 4% in one group of individuals.[26]

There are many other methods used to determine body fat percentage. Hydrostatic weighing, one

of the most accurate methods of body fat calculation, involves weighting a person underwater.

Two other simpler and less accurate methods have been used historically but are now not

recommended.[27] The first is the skinfold test, in which a pinch of skin is precisely measured to

determine the thickness of the subcutaneous fat layer.[28] The other is bioelectrical impedance

analysis which uses electrical resistance. Bioelectrical impedance has not been shown to provide

an advantage over BMI.[29]

Body fat percentage measurement techniques used mainly for research include computed

tomography (CT scan), magnetic resonance imaging (MRI), and dual energy X-ray

absorptiometry (DEXA).[20] These techniques provide very accurate measurements, but it can be

difficult to obtain in the severely obese due to weight limits of most equipment and insufficient

diameter of many CT or MRI scanners.[30]

7

Childhood obesity

Variations in apparent body fat among children

The healthy BMI range varies with the age and sex of the child. Obesity in children and

adolescents is defined as a BMI greater than the 95th percentile.[31] The reference data that these

percentiles are based on is from 1963 to 1994 and thus has not been affected by the recent

increases in rates of obesity.[32]

Childhood obesity has reached epidemic proportions in 21st century with rising rates in both the

developed and developing world.[citation needed] Rates of obesity in Canadian boys have increased

from 11% in 1980s to over 30% in 1990s, while during this same time period rates increased

from 4 to 14% in Brazilian children.[33]

As with obesity in adults many different factors contribute to the rising rates of childhood

obesity. Changing diet and decreasing physical activity are believed to be the two most important

in causing the recent increase in the rate of obesity. Activities from self propelled transport, to

school physical education, and organized sports has been declining in many countries.[34]

8

Because childhood obesity often persists into adulthood, and is associated with numerous

chronic illnesses, it is important that children who are obese be tested for hypertension, diabetes,

hyperlipidemia, and fatty liver.[35]

Treatments used in children are primarily lifestyle interventions and behavioral techniques.

Medications are not FDA approved for use in this age group.[33]

Obesity is a medical condition in which excess body fat has accumulated to the extent that it may

have an adverse effect on health.[1] It is defined by body mass index (BMI) and further evaluated

in terms of fat distribution via the waist–hip ratio and total cardiovascular risk factors.[10][11] BMI

is closely related to both percentage body fat and total body fat.[12]

The most commonly used definitions, established by the World Health Organization (WHO) in

1997 and published in 2000, provide the values listed in the table at right.[3]

Some modifications to the WHO definitions have been made by particular bodies. The surgical

literature breaks down "class III" obesity into further categories whose exact values are still

disputed.[15]

Any BMI ≥ 35 or 40 is severe obesity

A BMI of ≥ 35 or 40–44.9 or 49.9 is morbid obesity

A BMI of ≥ 45 or 50 is super obesity

As Asian populations develop negative health consequences at a lower BMI than Caucasians,

some nations have redefined obesity; the Japanese have defined obesity as any BMI greater than

25[16] while China uses a BMI of greater than 28.[17]

Effects on health

Excessive body weight is associated with various diseases, particularly cardiovascular diseases,

diabetes mellitus type 2, obstructive sleep apnea, certain types of cancer, and osteoarthritis.[2] As

a result, obesity has been found to reduce life expectancy.[2]

9

Mortality

Relative risk of death over 10 years for White men (left) and women (right) who have never

smoked in the United States by BMI.[18]

Obesity is one of the leading preventable causes of death worldwide.[8][19][20] Large-scale

American and European studies have found that mortality risk is lowest at a BMI of 20–

25 kg/m2[18][21] in non-smokers and at 24–27 kg/m2 in current smokers, with risk increasing along

with changes in either direction.[22][23] A BMI above 32 has been associated with a doubled

mortality rate among women over a 16-year period.[24] In the United States obesity is estimated to

cause an excess 111,909 to 365,000 deaths per year,[2][20] while 1 million (7.7%) of deaths in the

European Union are attributed to excess weight.[25][26] On average, obesity reduces life

expectancy by six to seven years:[2][27] a BMI of 30–35 reduces life expectancy by two to

four years,[21] while severe obesity (BMI > 40) reduces life expectancy by 10 years.[21]

Morbidity

Obesity increases the risk of many physical and mental conditions. These comorbidities are most

commonly shown in metabolic syndrome,[2] a combination of medical disorders which includes:

10

diabetes mellitus type 2, high blood pressure, high blood cholesterol, and high triglyceride levels.[28]

Complications are either directly caused by obesity or indirectly related through mechanisms

sharing a common cause such as a poor diet or a sedentary lifestyle. The strength of the link

between obesity and specific conditions varies. One of the strongest is the link with type 2

diabetes. Excess body fat underlies 64% of cases of diabetes in men and 77% of cases in women.[29]

Health consequences fall into two broad categories: those attributable to the effects of increased

fat mass (such as osteoarthritis, obstructive sleep apnea, social stigmatization) and those due to

the increased number of fat cells (diabetes, cancer, cardiovascular disease, non-alcoholic fatty

liver disease).[2][30] Increases in body fat alter the body's response to insulin, potentially leading to

insulin resistance. Increased fat also creates a proinflammatory state,[31][32] and a prothrombotic

state.[30][33]

Medical field Condition Medical field Condition

Cardiology

ischemic heart disease :[34]

angina and myocardial

infarction

congestive heart failure [2]

high blood pressure [2]

abnormal cholesterol

levels [2]

deep vein thrombosis and

pulmonary embolism [35]

Dermatology

stretch marks [36]

acanthosis

nigricans [36]

lymphedema [36]

cellulitis [36]

hirsutism [36]

intertrigo [37]

Endocrinology

and

Reproductive

diabetes mellitus [2]

polycystic ovarian

syndrome [2]

Gastrointestinal gastroesophageal

reflux disease [2] [39]

11

medicine

menstrual disorders[2]

infertility [2] [38]

complications during

pregnancy [2] [38]

birth defects [2]

intrauterine fetal death [38]

fatty liver disease [2]

cholelithiasis

(gallstones)[2]

Neurology

stroke [2]

meralgia paresthetica [40]

migraines [41]

carpal tunnel syndrome [42]

dementia [43]

idiopathic intracranial

hypertension [44]

multiple sclerosis [45]

Oncology [46]

breast , ovarian

esophageal ,

colorectal

liver , pancreatic

gallbladder , stomach

endometrial , cervical

prostate , kidney

non-Hodgkin's

lymphoma, multiple

myeloma

Psychiatry depression in women[2]

social stigmatization [2]

Respirology obstructive sleep

apnea [2] [47]

obesity

hypoventilation

syndrome [2] [47]

asthma [2] [47]

increased

12

complications during

general anaesthesia [2] [5]

Rheumatology

and

Orthopedics

gout [48]

poor mobility[49]

osteoarthritis [2]

low back pain [50]

Urology and

Nephrology

erectile

dysfunction [51]

urinary

incontinence [52]

chronic renal

failure [53]

hypogonadism [54]

Survival paradox

Although the negative health consequences of obesity in the general population are well

supported by the available evidence, health outcomes in certain subgroups seem to be improved

at an increased BMI, a phenomenon known as the obesity survival paradox.[55] The paradox was

first described in 1999 in overweight and obese people undergoing hemodialysis,[55] and has

subsequently been found in those with heart failure and peripheral artery disease (PAD).[56]

In people with heart failure, those with a BMI between 30.0 and 34.9 had lower mortality than

those with a normal weight. This has been attributed to the fact that people often lose weight as

they become progressively more ill.[57] Similar findings have been made in other types of heart

disease. People with class I obesity and heart disease do not have greater rates of further heart

problems than people of normal weight who also have heart disease. In people with greater

degrees of obesity, however, risk of further events is increased.[58][59] Even after cardiac bypass

surgery, no increase in mortality is seen in the overweight and obese.[60] One study found that the

improved survival could be explained by the more aggressive treatment obese people receive

after a cardiac event.[61] Another found that if one takes into account chronic obstructive

pulmonary disease (COPD) in those with PAD the benefit of obesity no longer exists.[56]

13

Causes

At an individual level, a combination of excessive food energy intake and a lack of physical

activity is thought to explain most cases of obesity.[62] A limited number of cases are due

primarily to genetics, medical reasons, or psychiatric illness.[63] In contrast, increasing rates of

obesity at a societal level are felt to be due to an easily accessible and palatable diet, [64] increased

reliance on cars, and mechanized manufacturing.[65][66]

A 2006 review identified ten other possible contributors to the recent increase of obesity: (1)

insufficient sleep, (2) endocrine disruptors (environmental pollutants that interfere with lipid

metabolism), (3) decreased variability in ambient temperature, (4) decreased rates of smoking,

because smoking suppresses appetite, (5) increased use of medications that can cause weight

gain (e.g., atypical antipsychotics), (6) proportional increases in ethnic and age groups that tend

to be heavier, (7) pregnancy at a later age (which may cause susceptibility to obesity in children),

(8) epigenetic risk factors passed on generationally, (9) natural selection for higher BMI, and

(10) assortative mating leading to increased concentration of obesity risk factors (this would

increase the number of obese people by increasing population variance in weight).[67] While there

is substantial evidence supporting the influence of these mechanisms on the increased prevalence

of obesity, the evidence is still inconclusive, and the authors state that these are probably less

influential than the ones discussed in the previous paragraph.

Diet

Map of dietary energy availability per person per day in 1961 (left) and 2001–2003 (right) in kcal/person/day.[68]

  no data

  <1600

  1600–1800

  1800–2000

  2600–2800

  2800–3000

  3000–3200

  3200–3400

14

  2000–2200

  2200–2400

  2400–2600

  3400–3600

  >3600

Average per capita energy consumption of the world from 1961 to 2002[68]

The per capita dietary energy supply varies markedly between different regions and countries. It

has also changed significantly over time.[68] From the early 1970s to the late 1990s the average

calories available per person per day (the amount of food bought) increased in all parts of the

world except Eastern Europe. The United States had the highest availability with 3,654 calories

per person in 1996.[68] This increased further in 2003 to 3,754.[68] During the late 1990s

Europeans had 3,394 calories per person, in the developing areas of Asia there were

2,648 calories per person, and in sub-Saharan Africa people had 2,176 calories per person.[68][69]

Total calorie consumption has been found to be related to obesity.[70]

The widespread availability of nutritional guidelines [71] has done little to address the problems of

overeating and poor dietary choice.[72] From 1971 to 2000, obesity rates in the United States

increased from 14.5% to 30.9%.[73] During the same period, an increase occurred in the average

amount of food energy consumed. For women, the average increase was 335 calories per day

(1,542 calories in 1971 and 1,877 calories in 2004), while for men the average increase was

168 calories per day (2,450 calories in 1971 and 2,618 calories in 2004). Most of this extra food

energy came from an increase in carbohydrate consumption rather than fat consumption.[74] The

primary sources of these extra carbohydrates are sweetened beverages, which now account for

almost 25 percent of daily food energy in young adults in America, [75] and potato chips.[76]

Consumption of sweetened drinks is believed to be contributing to the rising rates of obesity. [77]

[78]

15

As societies become increasingly reliant on energy-dense, big-portions, and fast-food meals, the

association between fast-food consumption and obesity becomes more concerning.[79] In the

United States consumption of fast-food meals tripled and food energy intake from these meals

quadrupled between 1977 and 1995.[80]

Agricultural policy and techniques in the United States and Europe have led to lower food prices.

In the United States, subsidization of corn, soy, wheat, and rice through the U.S. farm bill has

made the main sources of processed food cheap compared to fruits and vegetables.[81]

Obese people consistently under-report their food consumption as compared to people of normal

weight.[82] This is supported both by tests of people carried out in a calorimeter room[83] and by

direct observation.

Sedentary lifestyle

A sedentary lifestyle plays a significant role in obesity.[84] Worldwide there has been a large shift

towards less physically demanding work,[85][86][87] and currently at least 60% of the world's

population gets insufficient exercise.[86] This is primarily due to increasing use of mechanized

transportation and a greater prevalence of labor-saving technology in the home.[85][86][87] In

children, there appear to be declines in levels of physical activity due to less walking and

physical education.[88] World trends in active leisure time physical activity are less clear. The

World Health Organization indicates people worldwide are taking up less active recreational

pursuits, while a study from Finland[89] found an increase and a study from the United States

found leisure-time physical activity has not changed significantly.[90]

In both children and adults, there is an association between television viewing time and the risk

of obesity.[91][92][93] A 2008 meta-analysis found 63 of 73 studies (86%) showed an increased rate

of childhood obesity with increased media exposure, with rates increasing proportionally to time

spent watching television.[94]

Genetics

16

Like many other medical conditions, obesity is the result of an interplay between genetic and

environmental factors. Polymorphisms in various genes controlling appetite and metabolism

predispose to obesity when sufficient food energy present. As of 2006 more than 41 of these sites

have been linked to the development of obesity when a favorable environment is present.[96]

People with two copies of the FTO gene (fat mass and obesity associated gene) has been found

on average to weigh 3–4 kg more and have a 1.67-fold greater risk of obesity compared to those

without the risk allele.[97] The percentage of obesity that can be attributed to genetics varies,

depending on the population examined, from 6% to 85%.[98]

Obesity is a major feature in several syndromes, such as Prader-Willi syndrome, Bardet-Biedl

syndrome, Cohen syndrome, and MOMO syndrome. (The term "non-syndromic obesity" is

sometimes used to exclude these conditions.)[99] In people with early-onset severe obesity

(defined by an onset before 10 years of age and body mass index over three standard deviations

above normal), 7% harbor a single point DNA mutation.[100]

Studies that have focused upon inheritance patterns rather than upon specific genes have found

that 80% of the offspring of two obese parents were obese, in contrast to less than 10% of the

offspring of two parents who were of normal weight.[101]

The thrifty gene hypothesis postulates that due to dietary scarcity during human evolution people

are prone to obesity. Their ability to take advantage of rare periods of abundance by storing

energy as fat would be advantageous during times of varying food availability, and individuals

with greater adipose reserves would be more likely survive famine. This tendency to store fat,

however, would be maladaptive in societies with stable food supplies.[102] This theory has

received various criticisms and other evolutionarily based theories such as the drifty gene

hypothesis and the thrifty phenotype hypothesis have also been proposed.[103][104]

Medical and psychiatric illness

Certain physical and mental illnesses and the pharmaceutical substances used to treat them can

increase risk of obesity. Medical illnesses that increase obesity risk include several rare genetic

syndromes (listed above) as well as some congenital or acquired conditions: hypothyroidism,

17

Cushing's syndrome, growth hormone deficiency,[105] and the eating disorders: binge eating

disorder and night eating syndrome.[2] However, obesity is not regarded as a psychiatric disorder,

and therefore is not listed in the DSM-IVR as a psychiatric illness.[106] The risk of overweight and

obesity is higher in patients with psychiatric disorders than in persons without psychiatric

disorders.[107]

Certain medications may cause weight gain or changes in body composition; these include

insulin, sulfonylureas, thiazolidinediones, atypical antipsychotics, antidepressants, steroids,

certain anticonvulsants (phenytoin and valproate), pizotifen, and some forms of hormonal

contraception.[2]

Social determinants

While genetic influences are important to understanding obesity, they cannot explain the current

dramatic increase seen within specific countries or globally. [108] Though it is accepted that energy

consumption in excess of energy expenditure leads to obesity on an individual basis, the cause of

the shifts in these two factors on the societal scale is much debated. There are a number of

theories as to the cause but most believe it is a combination of various factors.

The correlation between social class and BMI varies globally. A review in 1989 found that in

developed countries women of a high social class were less likely to be obese. No significant

differences were seen among men of different social classes. In the developing world, women,

men, and children from high social classes had greater rates of obesity. [109] An update of this

review carried out in 2007 found the same relationships, but they were weaker. The decrease in

strength of correlation was felt to be due to the effects of globalization.[110] Among developed

countries, levels of adult obesity, and percentage of teenage children who are overweight, are

correlated with income inequality. A similar relationship is seen among US states: more adults,

even in higher social classes, are obese in more unequal states.[111]

Many explanations have been put forth for associations between BMI and social class. It is

thought that in developed countries, the wealthy are able to afford more nutritious food, they are

under greater social pressure to remain slim, and have more opportunities along with greater

18

expectations for physical fitness. In undeveloped countries the ability to afford food, high energy

expenditure with physical labor, and cultural values favoring a larger body size are believed to

contribute to the observed patterns.[110] Attitudes toward body mass held by people in one's life

may also play a role in obesity. A correlation in BMI changes over time has been found among

friends, siblings, and spouses.[112] Stress and perceived low social status appear to increase risk of

obesity.[111][113][114]

Smoking has a significant effect on an individual's weight. Those who quit smoking gain an

average of 4.4 kilograms (9.7 lb) for men and 5.0 kilograms (11.0 lb) for women over ten years.[115] However, changing rates of smoking have had little effect on the overall rates of obesity.[116]

In the United States the number of children a person has is related to their risk of obesity. A

woman's risk increases by 7% per child, while a man's risk increases by 4% per child. [117] This

could be partly explained by the fact that having dependent children decreases physical activity

in Western parents.[118]

In the developing world urbanization is playing a role in increasing rate of obesity. In China

overall rates of obesity are below 5%; however, in some cities rates of obesity are greater than

20%.[119]

Malnutrition in early life is believed to play a role in the rising rates of obesity in the developing

world.[120] Endocrine changes that occur during periods of malnutrition may promote the storage

of fat once more food energy becomes available.[120]

Consistent with cognitive epidemiological data, numerous studies confirm that obesity is

associated with cognitive deficits. [121] Whether obesity causes cognitive deficits, or vice versa is

unclear at present.

Infectious agents

The study of the effect of infectious agents on metabolism is still in its early stages. Gut flora has

been shown to differ between lean and obese humans. There is an indication that gut flora in

obese and lean individuals can affect the metabolic potential. This apparent alteration of the

19

metabolic potential is believed to confer a greater capacity to harvest energy contributing to

obesity. Whether these differences are the direct cause or the result of obesity has yet to be

determined unequivocally.[122]

An association between viruses and obesity has been found in humans and several different

animal species. The amount that these associations may have contributed to the rising rate of

obesity is yet to be determined.[123]

Pathophysiology

A comparison of a mouse unable to produce leptin thus resulting in obesity (left) and a normal

mouse (right)

Flier summarizes the many possible pathophysiological mechanisms involved in the

development and maintenance of obesity.[124] This field of research had been almost

unapproached until leptin was discovered in 1994. Since this discovery, many other hormonal

mechanisms have been elucidated that participate in the regulation of appetite and food intake,

storage patterns of adipose tissue, and development of insulin resistance. Since leptin's

discovery, ghrelin, insulin, orexin, PYY 3-36, cholecystokinin, adiponectin, as well as many

other mediators have been studied. The adipokines are mediators produced by adipose tissue;

their action is thought to modify many obesity-related diseases.

Leptin and ghrelin are considered to be complementary in their influence on appetite, with

ghrelin produced by the stomach modulating short-term appetitive control (i.e. to eat when the

stomach is empty and to stop when the stomach is stretched). Leptin is produced by adipose

20

tissue to signal fat storage reserves in the body, and mediates long-term appetitive controls (i.e.

to eat more when fat storages are low and less when fat storages are high). Although

administration of leptin may be effective in a small subset of obese individuals who are leptin

deficient, most obese individuals are thought to be leptin resistant and have been found to have

high levels of leptin.[125] This resistance is thought to explain in part why administration of leptin

has not been shown to be effective in suppressing appetite in most obese people.[124]

A graphic depiction of a leptin molecule

While leptin and ghrelin are produced peripherally, they control appetite through their actions on

the central nervous system. In particular, they and other appetite-related hormones act on the

hypothalamus, a region of the brain central to the regulation of food intake and energy

expenditure. There are several circuits within the hypothalamus that contribute to its role in

integrating appetite, the melanocortin pathway being the most well understood.[124] The circuit

begins with an area of the hypothalamus, the arcuate nucleus, that has outputs to the lateral

hypothalamus (LH) and ventromedial hypothalamus (VMH), the brain's feeding and satiety

centers, respectively.[126]

The arcuate nucleus contains two distinct groups of neurons.[124] The first group coexpresses

neuropeptide Y (NPY) and agouti-related peptide (AgRP) and has stimulatory inputs to the LH

and inhibitory inputs to the VMH. The second group coexpresses pro-opiomelanocortin (POMC)

and cocaine- and amphetamine-regulated transcript (CART) and has stimulatory inputs to the

VMH and inhibitory inputs to the LH. Consequently, NPY/AgRP neurons stimulate feeding and

inhibit satiety, while POMC/CART neurons stimulate satiety and inhibit feeding. Both groups of

arcuate nucleus neurons are regulated in part by leptin. Leptin inhibits the NPY/AgRP group

21

while stimulating the POMC/CART group. Thus a deficiency in leptin signaling, either via leptin

deficiency or leptin resistance, leads to overfeeding and may account for some genetic and

acquired forms of obesity.[124]

Public health

The World Health Organization (WHO) predicts that overweight and obesity may soon replace

more traditional public health concerns such as undernutrition and infectious diseases as the most

significant cause of poor health.[127] Obesity is a public health and policy problem because of its

prevalence, costs, and health effects.[128] Public health efforts seek to understand and correct the

environmental factors responsible for the increasing prevalence of obesity in the population.

Solutions look at changing the factors that cause excess food energy consumption and inhibit

physical activity. Efforts include federally reimbursed meal programs in schools, limiting direct

junk food marketing to children,[129] and decreasing access to sugar-sweetened beverages in

schools.[130] When constructing urban environments, efforts have been made to increase access to

parks and to develop pedestrian routes.[131]

Many countries and groups have published reports pertaining to obesity. In 1998 the first US

Federal guidelines were published, titled "Clinical Guidelines on the Identification, Evaluation,

and Treatment of Overweight and Obesity in Adults: The Evidence Report".[132] In 2006 the

Canadian Obesity Network published the "Canadian Clinical Practice Guidelines (CPG) on the

Management and Prevention of Obesity in Adults and Children". This is a comprehensive

evidence-based guideline to address the management and prevention of overweight and obesity

in adults and children.[133]

In 2004, the United Kingdom Royal College of Physicians, the Faculty of Public Health and the

Royal College of Paediatrics and Child Health released the report "Storing up Problems", which

highlighted the growing problem of obesity in the UK.[134] The same year, the House of

Commons Health Select Committee published its "most comprehensive inquiry [...] ever

undertaken" into the impact of obesity on health and society in the UK and possible approaches

to the problem.[135] In 2006, the National Institute for Health and Clinical Excellence (NICE)

22

issued a guideline on the diagnosis and management of obesity, as well as policy implications for

non-healthcare organizations such as local councils.[136]

A 2007 report produced by Sir Derek Wanless for the King's Fund warned that unless further

action was taken, obesity had the capacity to cripple the National Health Service financially.[137]

In the United States organizations such as the Bill Clinton Foundation's Alliance for a Healthier

Generation and Action for Healthy Kids are working to combat childhood obesity. Additionally,

the Centers for Disease Control and Prevention co-hosted the first-ever Weight of the Nation

Conference in 2009 with the goal of focusing national attention on the obesity epidemic.[138]

Comprehensive approaches are being looked at to address the rising rates of obesity. The Obesity

Policy Action (OPA) framework divides measure into 'upstream' policies, 'midstream' policies,

'downstream' policies. 'Upstream' policies look at changing society, 'midstream' policies try to

alter individuals' behavior to prevent obesity, and 'downstream' policies try to treat currently

afflicted people.[139]

23

LITERATURE REVIEWS

24

LITERATURE REVIEW

1. Bhargava, Alok; Guthrie, J. (2002). "Unhealthy eating habits, physical exercise and

macronutrient intakes are predictors of anthropometric indicators in the Women's Health

Trial: Feasibility Study in Minority Populations". British Journal of Nutrition 88 (6):

719–728. doi:10.1079/BJN2002739. PMID 12493094.

2. Bhargava, Alok (2006). "Fiber intakes and anthropometric measures are predictors of

circulating hormone, triglyceride, and cholesterol concentration in the Women's Health

Trial". Journal of Nutrition 136 (8): 2249–2254. PMID 16857849.

3. Jebb S. and Wells J. Measuring body composition in adults and children In:Peter G.

Kopelman, Ian D. Caterson, Michael J. Stock, William H. Dietz (2005). Clinical obesity

in adults and children: In Adults and Children. Blackwell Publishing. pp. 12–28.

ISBN 140-511672-2.

4. Kopelman P., Caterson I. An overview of obesity management In:Peter G. Kopelman, Ian

D. Caterson, Michael J. Stock, William H. Dietz (2005). Clinical obesity in adults and

children: In Adults and Children. Blackwell Publishing. pp. 319–326. ISBN 140-511672-

2.

5. National Heart, Lung, and Blood Institute (NHLBI) (1998) (PDF). Clinical Guidelines on

the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults.

International Medical Publishing, Inc. ISBN 1-58808-002-1.

http://www.nhlbi.nih.gov/guidelines/obesity/ob_gdlns.pdf.

6. "Obesity: guidance on the prevention, identification, assessment and management of

overweight and obesity in adults and children" (pdf). National Institute for Health and

Clinical Excellence(NICE). National Health Services (NHS). 2006.

http://www.nice.org.uk/nicemedia/pdf/CG43NICEGuideline.pdf. Retrieved April 8,

2009.

7. Puhl R., Henderson K., and Brownell K. Social consequences of obesity In:Peter G.

Kopelman, Ian D. Caterson, Michael J. Stock, William H. Dietz (2005). Clinical obesity

in adults and children: In Adults and Children. Blackwell Publishing. pp. 29–45.

ISBN 140-511672-2.

25

8. Seidell JC. Epidemiology — definition and classification of obesity In:Peter G.

Kopelman, Ian D. Caterson, Michael J. Stock, William H. Dietz (2005). Clinical obesity

in adults and children: In Adults and Children. Blackwell Publishing. pp. 3–11.

ISBN 140-511672-2.

9. World Health Organization (WHO) (2000) (PDF). Technical report series 894: Obesity:

Preventing and managing the global epidemic.. Geneva: World Health Organization.

ISBN 92-4-120894-5. http://whqlibdoc.who.int/trs/WHO_TRS_894_(part1).pdf.

10. A Okyar , A Can, N Akev, G Baktir, N Sütlüpinar Effect of Aloe vera leaves on blood

glucose level in type I and type II diabetic rat models. Aloe vera (L.) Burm. fil.(= A.

barbadensis Miller)(Liliaceae) is native to North Africa and also cultivated in Turkey.

Aloes have long been used all over the world for their various medicinal properties. In the

past 15 years, there have been controversial reports on the hypoglycaemic activity of

Aloe species, probably due to differences in the parts of the plant used or to the model of

diabetes chosen. In this study, separate experiments on three main groups of rats, namely,

non-diabetic (ND), type I (IDDM) and type II (NIDDM) diabetic rats were carried out. A.

vera leaf pulp and gel extracts were ineffective on lowering the blood sugar level of ND

rats. A. vera leaf pulp extract showed hypoglycaemic activity on IDDM and NIDDM rats,

the effectiveness being enhanced for type II diabetes in comparison with glibenclamide.

On the contrary, A. vera leaf gel extract showed hyperglycaemic activity on NIDDM rats.

It may therefore be concluded that the pulps of Aloe vera leaves devoid of the gel could

be useful in the treatment of non-insulin dependent diabetes mellitus

11. Y Ozsoy, T Tunçel, A Can, N Akev, S Birteksöz, A Gerçeker

Department of Pharmaceutical Technology, Faculty of Pharmacy, Istanbul University,

TurkeyGel formulations of ciprofloxacin hydrochloride (CPH) were prepared with

bioadhesive polymers such as hydroxypropyl methylcellulose (HPMC), hydroxyethyl

cellulose (HEC) and methylcellulose (MC). They were administered into the nasal cavity

of rabbits. A nasal aqueous suspension of CPH with glycerol was also applied. In

addition, the effect of Tween 80 as penetration enhancer was examined. The agar plate

diffusion technique was applied for the assay of CPH. The results were compared with

oral and intravenous administrations. The bioavailability of the CPH gel formulation

26

prepared with HPMC was almost identical to that of the oral route. Other nasal

formulations with HEC and MC had bioavailabilities lower than oral preparations. The

relative bioavailabilities for the formulation containing HEC and MC were 48.7 and

45.54%, respectively. To increase the bioavailabilities, 1%(w/w) of Tween 80 was added.

The bioavailability of these gel formulations increased to 63.54 and 55.72%, respectively.

Experiments carried out on rabbits showed that the nasal administration of CPH

bioadhesive gel formulation containing HPMC may be an alternative to the oral route.

12. N Akev, A Can The separation and partial purification of two lectins from the leaf pulp

of Aloe vera L.(=barbadensis Miller) is presented. The fraction showing

haemagglutinating activity was precipitated at 50% ammonium sulphate concentration

from the crude leaf pulp extract. The precipitate thus obtained, after dialysis, was applied

to a hydroxylapatite column. Stepwise elution resulted in two peaks showing

haemagglutinating activity eluted with 5 mM (Aloctin I) and 20 mM (Aloctin II)

phosphate buffers. Haemagglutinating activity was estimated visually by adding a 4%

rabbit erythrocyte suspension to serial two-fold dilutions of the lectins in microtitration

plates. None of the 20 sugars tested inhibited haemag--glutinating activity of Aloctin I up

a concentration of 500 mM. Aloctin II was inhibited by N-acetyl-D--galactosamine at

250 mM concentration. Of 10 metal ions tested, only Al(3+) salts were found to activate

Aloctin I and II. On the other hand, it was shown that neither lectin possessed any alpha-

and beta- galactosidase or alpha- and beta- glucosidase activity. The lectins were of

glycoprotein structure containing approximately 5% neutral sugar. The specificity of the

lectins towards human and rat erythrocytes was investigated.

13. H Spahn-Langguth, G Baktir, A Radschuweit, A Okyar, B Terhaag, P Ader, A Hanafy,

P Langguth Among the different application routes peroral administration remains the

one most widely used. Hence, mechanisms affecting p.o. bioavailability are of particular

interest, also in drug development. In recent years, intestinal drug secretion mediated by

the multi-drug resistance gene product P-glycoprotein (Pgp) has been discovered as a

possible mechanism of low and erratic bioavailability. Due to the saturability of this

process, a dose-dependent apparent oral clearance may be observed which decreases

upon increasing dose. However, in vivo intestinal secretion might be revealed only in the

27

lower or subtherapeutic dose range. In permeability studies with Caco-2 cell monolayers,

the MDR-reversing agent verapamil inhibits secretion of P-glycoprotein substrates and,

hence, increases apical-to-basolateral permeability. The aim of the rat studies with

talinolol presented here was to test the relevance of the intestinal secretion process as

well as the extent of inhibition by verapamil in ex vivo, in situ, and in vivo

talinolol/verapamil drug-drug interaction studies. Intestinal secretion of talinolol was

detected indirectly in ex vivo studies via transport inhibition with verapamil and directly

in in situ intestinal perfusions in rats following a talinolol i.v. bolus. Both i.v. and p.o.

verapamil appear to affect the concentration-time profiles of talinolol. Relevant

observations with respect to drug absorption are the decreased apparent oral clearance

upon verapamil coadministration as well as the decreased tmax and mean absorption

times at high verapamil doses. Talinolol may be regarded as a potential model compound

for mechanistic studies on Pgp interactions, including permeability as well as binding

studies and the involvement of transporters other than Pgp.

14. H Gezginci, S Salman, A Okyar, G Baktir Adipocyte differentiation defect in

mesenchymal stromal cells of patients with malignant infantile osteopetrosis. Malignant

infantile osteopetrosis (MIOP) is a disorder of osteoclasts characterized by defective bone

resorption and death in infancy. The multipotent mesenchymal stromal cells (MSC) and

their progeny (osteoblasts) are major components of the bone marrow (BM)

microenvironment and are found in close contact with cells of hematopoietic origin,

including osteoclasts. We hypothesized that MSC defects may be associated with

osteoclast dysfunction and osteopetrosis phenotype. Methods BM MSC, obtained from

six patients with MIOP, were expanded in vitro and characterized by morphology,

plastic-adherence, immunophenotype and multilineage differentiation potential. Results

Physical and immunophenotypic characteristics of patient MSC were similar to healthy

age-matched controls. However, an isolated in vitro differentiation defect toward

adipogenic lineage was demonstrated in patient MSC and confirmed by low or absent

expression of adipogenic transcripts (peroxisome proliferator-activated receptor-gamma,

adipophilin, stearoyl-CoA desaturase, leptin and adiponectin) upon induction of

adipogenesis. Following BM transplantation, minimal improvement in adipogenic

28

potency of MSC was demonstrated by Oil Red O staining. Discussion MIOP is associated

in vitro with a failure of MSC to differentiate into an adipogenic lineage, suggesting a

BM microenvironment defect. The defect may contribute to osteoclast dysfunction, or

may be attributed to the effect of the osteopetrotic marrow environment.

15. H Narasimha-Iyer, A Can, B Roysam, J Stern :Detection and analysis of changes from

retinal images is important in clinical practice, quantitative scoring of clinical trials,

computer-assisted reading centers, and in medical research. This paper presents a fully-

automated approach for robust detection and classification of changes in longitudinal

time-series of fluorescein angiograms (FA). The changes of interest here are related to the

development of choroidal neo-vascularization (CNV) in wet macular degeneration.

Specifically, the changes in CNV regions as well as the retinal pigment epithelium (RPE)

hypertrophic regions are detected and analyzed to study the progression of disease and

effect of treatment. Retinal features including the vasculature, vessel branching/crossover

locations, optic disk and location of the fovea are first segmented automatically. The

images are then registered to sub-pixel accuracy using a 12-dimensional mapping that

accounts for the unknown retinal curvature and camera parameters. Spatial variations in

illumination are removed using a surface fitting algorithm that exploits the segmentations

of the various features. The changes are identified in the regions of interest and a

Bayesian classifier is used to classify the changes into clinically significant classes. The

automated change analysis algorithms were found to have a success rate of 83%

16. M Dartar Oztan, B Dogru Pekiner, A Can To assess the effects of exposure to 6

chemical agents on the permeability of latex gloves by dye permeability test and to

qualitatively evaluate the microscopic changes in the ultrastructure of the gloves. Method

and Materials: The middle fingers of 35 medium-sized, nonsterile latex gloves were used.

The chemical agents tested were eugenol, 5% NaOCl, 17% EDTA, 0.2% chlorhexidine

gluconate, Cresophene (Septodent), and Chlorispray (Anios). Following treatment for 15

minutes with each chemical agent, glove fingers were filled with 10 mL of 0.02%

erythrosine dye solution. Then the outer glove surface was washed with 10 mL of

distilled water at intervals of 15, 30, 45, and 60 minutes. A spectrophotometer was used

29

at 530-nm wavelength to determine the percentage of absorption from each collected

washing solution. The results were compared with the values obtained from untreated

gloves. Additionally, small pieces of the glove samples were examined by SEM to

determine whether any ultrastructural changes occurred upon exposure to the chemicals.

Results: The permeability of gloves was increased by exposure to Chlorispray and

Cresophene, but 5% NaOCl, 17% EDTA, and 0.2% chlorhexidine gluconate had no

effect. Major surface changes were noticed in NaOCl, EDTA, Cresophene, and

Chlorispray groups, while eugenol and chlorhexidine gluconate had minimal or no effect.

Conclusion: Damaging effects of chemical agents on latex gloves for penetration and

infection control should be considered by the dental practitioner.(Quintessence Int 2007;

17. P Cetinalp-Demircan, A Can, Selda Bekpinar, Y Unlucerci, Y Orhan This study was

performed to test whether plasma asymmetric dimethylarginine (ADMA) concentrations

are related to obesity and obesity complications including decrement in insulin sensitivity

and adiponectin levels, dyslipidemia and low-grade inflammation. Asymmetric

dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA) concentrations

were analyzed by HPLC in 17 overweight (BMI >/= 25 kg/m2) and 40 obese (BMI >/=

30 kg/m2) premenopausal women. Age-matched healthy women were studied as

controls. Obesity did not give rise to a significant change in circulating ADMA levels but

reduced in SDMA levels. As compared with control subjects (0.441 +/- 0.102 microM),

ADMA values in overweight and obese subjects were found to be as 0.412 +/- 0.102 and

0.436 +/- 0.093, respectively. No Pearson's association of ADMA with relevant risk

variables for cardiovascular disease, including blood pressure, insulin sensitivity,

inflammatory markers, lipid and adiponectin levels. However, in linear regression

analysis, BMI, diastolic blood pressure, glucose, insulin, and IL-8 emerged as significant

predictors of ADMA. In spite of obese women have elevated hs-CRP, triglyceride levels

and decreased insulin sensitivity, adiponectin and HDL-cholesterol levels, all of which is

closely linked risk factors for cardiovascular disease, circulating ADMA levels remained

unchanged in obese individuals as compared with controls.

18. A Can, H Narasimha-Iyer, B Roysam, J Stern Detection and analysis of changes from

retinal images is important in clinical practice, quantitative scoring of clinical trials,

30

computer-assisted reading centers, and in medical research. This paper presents a fully-

automated approach for robust detection and classification of changes in longitudinal

time-series of fluorescein angiograms (FA). The changes of interest here are related to the

development of choroidal neo-vascularization (CNV) in wet macular degeneration.

Specifically, the changes in CNV regions as well as the retinal pigment epithelium (RPE)

hypertrophic regions are detected and analyzed to study the progression of disease and

effect of treatment. Retinal features including the vasculature, vessel branching/crossover

locations, optic disk and location of the fovea are first segmented automatically. The

images are then registered to sub-pixel accuracy using a 12-dimensional mapping that

accounts for the unknown retinal curvature and camera parameters. Spatial variations in

illumination are removed using a surface fitting algorithm that exploits the segmentations

of the various features. The changes are identified in the regions of interest and a

Bayesian classifier is used to classify the changes into clinically significant classes. The

automated change analysis algorithms were found to have a success rate of 83%

19. F Kara, O Cinar, E Erdemli-Atabenli, B Tavil-Sabuncuoglu, A Can Background.

Pregnant endometrial stroma, an immunologically privileged site in the female

reproductive system, is enriched by decidual and natural killer (NK) cells. Since the

cellular microenvironment in early pregnancy from the decidual tissues of normal and

miscarriage cases has gained importance, with special emphasis on cell-to-cell contacts,

we aimed to document the plastic structure of the cellular milieu in normal and

miscarriage decidua. Methods. Endometrial biopsies were obtained from women after

legal curettage or women who had been treated by curettage after miscarriage. Samples

were analysed in a light microscope (LM), a scanning electron microscope (SEM) and a

transmission electron microscope (TEM). Results. Decidual cells possess several

polyploidic protrusions on cell membranes. NK cells were distributed among decidual

cells. Decidual cells were found to develop gap junctions in the interfaces between each

other. Their cytoplasms were also found to possess well-developed protein synthesising

organelles. Decidual cells obtained from miscarriages showed a moderate degree of

degeneration and, in between, a decreased number of junctional complexes. Mononuclear

cell infiltration was found to be significantly low. Conclusion. We conclude that decidual

31

cells during early pregnancy build a series of miniature cell-cell contacts to assemble a

proper endometrial milieu. In contrast, in miscarriage samples, those intercellular

communications seem lacking, associated with an increased number of NK cells, a

phenomenon which obviously alters proper implantation and leads to the induction of

embryonic disgenesis and miscarriage.

20. A A Fred-Jaiyesimi, M R Wilkins, K A Abo Suppressing the production of glucose by

inhibiting a-amylase / a-glucosidase activity is one of the therapeutic approaches for

decreasing postprandial hyperglycaemia and a strategy for evaluating antidiabetic

activity. We investigated leaves of Spondias mombin because our previous

ethnobotanical survey showed that it is used by traditional healers to manage diabetes in

South West Nigeria. We report a bioactivity-guided study of S. mombin using glucose

loading (1 g/kg) alloxan-induced diabetic rats and inhibition of a-amylase as basis for

isolation of active constituents. Hyperglycaemia was induced in albino rats and blood

glucose levels monitored for 180 mins using a glucometer. Powdered leaves were

macerated with 80% Methanol. The active extract was fractionated on column

chromatography packed with silica gel G6OA eluting with gradient mixtures of pet. ether

and ethylacetate. The most active a-amylase inhibiting fraction was purified on thin layer

chromatography (TLC) and pure compound identified by spectroscopy. Peak decrease in

blood glucose of 41.4%(p < 0.05) was recorded after 60 mins. This activity-guided study

produced an active TLC band (69.8% amylase inhibition, p < 0.05) from which a-

sitosterol was characterized as the main inhibitor. This is first report of hypoglycaemic

and amylase inhibitory activities of S. mombin. The role of phytosterols in control of

diabetes mellitus is discussed. This study justifies the ethnopharmacological use of this

species in recipes for management of diabetes mellitus.

21. Rajangam Udayakumar, Sampath Kasthurirengan, Ayyappan Vasudevan, Thankaraj

Salammal Mariashibu, Jesudass Joseph Sahaya Rayan, Chang Won Choi, Andy

Ganapathi, Sei Chang Kim The phenolic compounds and flavonoids were determined

from the extracts of Withania somnifera root (WSREt) and leaf (WSLEt). The WSREt

has 28.26 mg/g total phenolic compounds and 17.32 mg/g flavonoids, whereas WSLEt

32

has 5.4 mg/g total phenolic compounds and 5.1 mg/g flavonoids. The WSREt, WSLEt

and glibenclamide were orally administered daily to diabetic rats for 8 weeks. After the

treatment, the levels of urine sugar, blood glucose, liver glycogen, and antioxidants like

vitamin C and E in plasma and superoxide dismutase (SOD), catalase (CAT),

thiobarbituric acid reactive substances (TBARS), glutathione peroxidase (GPx),

glutathione-S-transferase (GST) and reduced glutathione (GSH) in liver, kidney and heart

were determined. Diabetic rats showed a significant (p < 0.05) elevation in glucose and

TBARS and a significant (p < 0.05) reduction in glycogen, vitamin C and E, SOD, CAT,

GPx, GST, and GSH levels when compared to normal control rats. Administration of

WSREt, WSLEt and glibenclamide to diabetic rats restored the levels to normal. In the

light of aforesaid facts, it is suggested that the presence of phenolic compounds including

flavonoids in W. somnifera root and leaf extracts and their antioxidant activity may play

a vital role in reduction of blood glucose level in alloxan-induced diabetic rats.

22. Mustafa Aslan, Nilüfer Orhan, Didem Deliorman Orhan, Fatma Ergun

Cydonia oblonga Mill.(Rosaceae) leaves, Helianthus tuberosus L.(Asteraceae) tubers, and

Allium porrum L.(Liliaceae) bulbs are used as a folk remedy for the treatment of diabetes

and they are also consumed as food in Turkey. In the present study, the antidiabetic and

antioxidant activities of the ethanol extracts of these plants were studied in normal and

streptozotocin-induced diabetic rats for 5 days. All extracts were administrated orally to

rats at the doses of 250 and 500mg/kg. Blood glucose level was measured according to

glucose oxidase method. In order to determine antioxidant activity, thiobarbituric acid

reactive substance (TBARS) and reduced glutathione (GSH) levels in liver, kidney, and

heart tissues were measured by using spectrophotometric methods. Oral administration of

C. oblonga (500mg/kg) and A. porrum (500mg/kg) extracts for 5 days in diabetic rats

caused a decrease in blood glucose levels by 33.8% and 18.0%, respectively. Moreover,

A. porrum and C. oblonga extracts induced significant alleviation on only heart tissue

TBARS levels (44.6 and 45.7%), H. tuberosus and A. porrum extracts showed an

inhibitory effect on kidney tissue TBARS levels (24.5 and 14.8%). None of the extracts

restored GSH levels in kidney, liver, and heart tissues of diabetic rats.

33

23. M-C Tchamadeu, P D D Dzeufiet, C C Kouambou Nouga, A G B Azebaze, J Allard, J-

P Girolami, I Tack, P Kamtchouing, T Dimo The stem bark of Mammea africana Sabine

(Guttifereae) is used in African rain forest to treat various diseases, including diabetes

mellitus. We investigated whether Mammea africana extract induced hypoglycaemic

activity in rats. MATERIALS AND METHODS: We tested the effects of acute (5hours)

and sub-acute (21 days) oral administrations of the CH(2)Cl(2)-MeOH stem bark extract

of Mammea africana (19 - 300mg/kg body weight) on blood glucose levels of normal and

streptozotocin (STZ)-induced type 1 diabetic rats. The effects were compared with those

of glibenclamide. RESULTS: Acute administration reduced blood glucose in the diabetic

rats only (33.87 %, P<0.01). Sub-acute treatment for 21 days also reduced blood glucose

level in diabetic rats (73.29 %, P<0.01). A reduction or stabilization in total serum

protein, triglyceride, cholesterol and alanine amino transferase levels was also observed.

No effect was observed on body weight loss but food and water intakes were significantly

reduced (P<0.01) in diabetic rats. The maximal anti-diabetic effect was obtained with the

dose of 75mg/kg and was more important than that of glibenclamide. CONCLUSION: It

can be concluded that extracts of Mammea africana exhibited a significant anti-

hyperglycaemic activity and improved the metabolic alterations in STZ-diabetic rats.

These results provide a rationale for the use of Mammea africana to treat diabetes

mellitus and hypercholesterolemia.

24. Ismet Ara Jahan, Nilufar Nahar, M Mosihuzzaman, Begum Rokeya, Liaquat Ali, A K

Azad Khan, Talat Makhmur, M Iqbal Choudhary The effects of Ficus racemosa Linn.

fruit extract and fraction on fasting serum glucose levels of normal, type 1 and type 2

diabetic model rats are presented. The aqueous 80% EtOH extract and its water soluble

fraction of F. racemosa fruit did not show any serum glucose lowering effect on non-

diabetic and type 2 diabetic rats at the fasting condition, whereas the extract showed

significant hypoglycaemic effect on the type 1 diabetic model rats. Both the extract and

fraction were consistently active in both non-diabetic and types 1 and 2 diabetic model

rats when fed simultaneously with glucose load. On the contrary, they were ineffective in

lowering blood glucose levels when fed 30 min prior to glucose load. The 1-BuOH

34

soluble part of the ethanol extract exhibited significant antioxidant activity in DPPH free

radical scavenging assay. 3-O-(E)-Caffeoyl quinate (1) was isolated for the first time

from this plant, which also showed significant antioxidant activity.

25. Vishalakshi D Devi, Asna Urooj Powdered leaves (500 mg/kg body weight) of

medicinal plants M. indica and C. igneus known to possess therapeutic effect were

supplemented to streptozotocin induced diabetic rats. Leaf powders of both the plants

were able to reduce blood glucose levels in the animals by 38 and 21% respectively after

15 days of supplementation. The preliminary results suggest that both the plants possess

potent hypoglycemic activity.

26. P Pavana, S Manoharan, G L Renju, S Sethupathy :Diabetes mellitus is a worldwide

leading metabolic syndrome, associated with profound alterations in carbohydrate, lipids,

lipoproteins and protein metabolisms. Worldwide, traditional practitioners for the

treatment of diabetes and its complications use a wide variety of medicinal plants. In the

present study the aqueous extract of Tephrosia purpurea leaves (TpALet) was evaluated

for its antihyperglycemic and antihyperlipidemic effects in streptozotocin induced

diabetic rats. Profound alterations in the concentrations of blood glucose, lipids and

lipoproteins were observed in diabetic rats. Oral administration of TpALet to diabetic rats

at a dose of 600 mg/kg body weight significantly reduced the level of blood glucose and

increased the level of plasma insulin as well as normalized the lipids and lipoproteins

profile. The present study thus demonstrated that TpALet has prominent

antihyperglycemic and antihyperlipidemic effects in streptozotocin induced diabetic rats.

27. Mohamed Eddouks, Mhamed Maghrani The purpose of this study was to determine the

mechanism underlying the hypoglycaemic activity of the aqueous extract perfusion of

Lepidium sativum L.(LS) in normal and streptozotocin-induced diabetic rats. The

aqueous LS extract was administered intravenously and the blood glucose levels were

determined within 4 h of treatment. Plasma insulin concentrations and glycosuria were

determined. The 24 h urinary transforming growth factor-beta1 (ELISA) was evaluated in

diabetic and control rats 15 days after oral treatment with the aqueous LS extract at a

dose of 20 mg/kg.The study showed that LS at a dose of 10 mg/kg/h reduced blood

glucose levels both in normal and diabetic rats (p < 0.001). At the same time as a potent

35

increase of glycosuria was observed both in normal and diabetic rats (p < 0.001). In

addition, oral administration of LS for 15 days normalized glycaemia (p < 0.001),

enhanced glycosuria (p < 0.05 vs diabetic control) and decreased the amount of urinary

TGF-beta1 (p < 0.01) in diabetic rats.It is concluded that the aqueous LS extract caused a

potent inhibition of renal glucose reabsorption which in turn reduced blood sugar. This

renal effect is at least one mechanism explaining the observed hypoglycaemic activity of

this plant in normal and diabetic rats.

28. Teresa Bobkiewicz-Kozłowska, Marzena Dworacka, Sebastian Kuczyński, Małgorzata

Abramczyk, Renata Kolanoś, Waleria Wysocka, Pedro M Garcia Lopez, Hanna

Winiarska The hypoglycaemic effects of two quinolizidine alkaloids: lupanine and 2-

thionosparteine were examined in non-diabetic and in streptozotocin-induced diabetic

rats. The model of experimental diabetes can be considered to be related to diabetes

mellitus type 2 with regards to the impairment of beta-cells' secretory function. A single

intraperitoneal injection of 2-thionosparteine at a dose of 8.6 mg/kg lowered the blood

glucose levels in diabetic rats at 90 and 120 min after administration and showed similar

hypoglycaemic effects to glibenclamide and sparteine, which were used as reference

substances. In contrast to glibenclamide, 2-thionosparteine did not result in a significant

increase in plasma insulin levels in diabetic rats; an increase was only observed in the

non-diabetic group. It was found that lupanine did not exert hypoglycaemic potency in

diabetic and in non-diabetic animals and did not significantly increase plasma insulin

concentration independent of the group examined. From this study we can state that 2-

thionosparteine, but not lupanine, is confirmed to be a possible plasma glucose lowering

agent. It is possible that 2-thionosparteine-dependent decrease in blood glucose level is

not the only result of this drug's related insulin secretion.

36

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