obesity sunil khare
TRANSCRIPT
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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