Lesson 4 : Nutrition Disorders
Obesity and health consequences
Physical Activity, Calories and Obesity:
The Challenge of Advances in Technology
 The epidemic of obesity, diabetes and the
metabolic syndrome
 Technology and reduced physical activity
 Technology and the availability of calories
 The need for integrated solutions
Obesity: definition
• Chronic disease characterized by
accumulation of fat. Obesity is defined as a
condition when ideal body weight is exceeded
by 20%
• Medical condition responsible for serious comorbidity and mortality.
Psychosocial consequence
• Economical impact of obesity
• Prejudice and Discrimination
• Considered lazy, incompetent and more often absent
due to illness
• Confronted with more problems at job application :
– Very few executive managers with overweight in the US
Epidemiology
Obesity rates:
USA
current and projected
England
Mauritius
50
Population percentage
with BMI > 30kg/m2
40
Australia
30
Brazil
20
10
0
1960
1970
1980
1990
2000
2010
2020
2030
Male and Female Obesity Levels in
Selected European Countries
Women
Men
Collated by the IOTF from recent surveys
Yugoslavia
Greece
Romania
Czech Rep.
England
Finland
Germany
Scotland
Slovakia
Portugal
Spain
Denmark
Belgium
Sweden
France
Italy
Netherlands
Norway
Hungary
Switzerland
% BMI >30
40
30
20
10
0
10
20
30
40
Prevalence of Obesity among
U.S. Adults, BRFSS, 1990
BMI = 30
Height Weight
152 (60) 69 (153)
167 (66) 84 (186)
178 (70) 94 (207)
(BMI > 30)
<10%
10-15%
>15%
Prevalence of Obesity among
U.S. Adults, BRFSS, 1991
<10%
10-15%
>15%
Prevalence of Obesity among
U.S. Adults, BRFSS, 1996
<10%
10-15%
>15%
Prevalence of Obesity among
U.S. Adults, BRFSS, 1999
Prevalence in 2000 = 30.5%
<10%
10-15%
>15%
The Developing Generations
1980s = X generation
1990s = Y generation
2000s = XXL generation
Diabetes Trends Among
Adults in the U.S., BRFSS 1990
<4%
4% -6%
Source: Mokdad et al., Diabetes Care 2000;23:1278-83.
Source: Mokdad et al., Diabetes Care 2000;23:1278-83.
>6%
Diabetes Trends Among
Adults in the U.S., BRFSS 1991-92
Source: Mokdad et al., Diabetes Care 2000;23:1278-83.
Diabetes Trends Among
Adults in the U.S., BRFSS 1995
Source: Mokdad et al., Diabetes Care 2000;23:1278-83.
Diabetes Trends Among
Adults in the U.S., BRFSS 2000
Source: Mokdad et al., J Am Med Assoc 2001;286(10).
What causes Obesity?
• Genetic predisposition
• Disruption in energy balance
• Environmental and social factors
The physiology of weight gain
Energy input
Energy output
Control factors
Genetic make-up
Diet
Exercise
Basal metabolism
Thermogenesis
Aetiology of obesity
LIFESTYLE
PSYCHOLOGICAL
MEDICAL
GENETIC
OBESITY
IA6
Thrifty genotype - feast and
famine theory
Those who are most efficient in storing
energy as fat during time of famine are
the survivors. Therefore that genetic
predisposition is favoured in a
population. When that population
experiences times of constant ‘feast’ i.e.
a western diet, they become obese and
develop diabetes.
GLUCOSE SENSING IN MATURITY
ONSET DIABETES OF THE YOUNG
GLUCOSE
HK
G6P
METABOLITES
NORMAL
BASAL
STATE
GLUCOSE
HK
G6P
METABOLITES
NORMAL
STIMULATION
OF INSULIN
SECRETION BY
HYPERGLYCEMIA
GLUCOSE
hk
G6P
METABOLITES
HYPERGLYCEMIA
SENSED AS
EUGLYCEMIA
IN MODY
Environmental effects on the risk
for type 2 diabetes mellitus
• Pima Indians living “on the rez” in Arizona have
among the highest prevalences of diabetes and
obesity of any group in the country.
• However, most of the Pima in Mexico are lean and
nondiabetic.
• The difference? The Mexican Pima still live a
subsistence lifestyle, farming beans and corn in the
arid mountains.
35
35
30
30
25
Diagnosed
0
0
Body Mass Index
Age 20-54 Years
Body Mass Index
Age 55-74 Years
>35
5
30-35
5
>35
10
30-35
10
25-30
15
22-25
15
25-30
20
Undiagnosed
22-25
20
<22
25
<22
Percent with Type 2 Diabetes
Prevalence of Type 2 Diabetes by Weight
The “Thrifty” Hypothesis
FAVORING
ENERGY
UTILIZATION
FAVORING
ENERGY
STORAGE
The Grasshopper
The Ant
FEAST
REPRODUCTIVE
ADVANTAGE
FAMINE
DEATH
FEAST
OBESITY/
DIABETES
FAMINE
SURVIVAL
Normal glucose tolerance
150
360
Plasma insulin (uU/ml)
Plasma glucose (mg/dl)
400
320
280
Normal
240
200
160
120
100
50
0
80
0
60
Time (min)
120
180
0
60
Time (min)
120
180
Impaired glucose tolerance:
Hyperinsulinemia and insulin resistance
150
Normal
360
Plasma insulin (uU/ml)
Plasma glucose (mg/dl)
400
320
Impaired glucose
tolerance
280
240
200
160
120
100
50
0
80
0
60
Time (min)
120
180
0
60
Time (min)
120
180
Glucose Disposal Rate (mg/M2/min)
Insulin Resistance in Type 2 DM
400
300
200
100
Control
Diabetes
0
10
100
1000
Insulin Concentration (uU/ml)
10000
INSULIN-STIMULATED GLUCOSE
UPTAKE IN MUSCLE AND FAT
UNDERSTANDING TYPE 2
DIABETES
LIPIDS
CARBOHYDRATE
WHICH IS THE CART AND
WHICH IS THE HORSE?
Is Insulin Resistance a Cause or
Effect of Diabetes?
• “Beta cell hyperresponsiveness is the earliest
event in the development of type 2 diabetes”
in rhesus monkeys, preceding the onset of
insulin resistance.
– Hansen and Bodkin, Am J Physiol 259:R612
(1990)
What does the “thrifty phenotype”
look like in a calorie restricted,
natural setting?
• Aboriginal Australians exposed to Western
diet/lifestyle develop type 2 diabetes and obesity in
alarming proportions, similar to native Americans.
• O’Dea has studied aboriginal Australians living in
the bush and has found:
– Lean individuals: average BMI 16 kg/m2
– They are relatively hypoglycemic (68 mg/dl) while having
relative hyperinsulinemia (13 uU/ml)
Fasting hyperinsulinemia predicts
type 2 diabetes independent of
insulin resistance
• Among 262 healthy Pima Indians, 48 (18%)
developed diabetes during a 4-6 year followup period.
• Fasting insulin and insulin responsiveness
predicted the development of diabetes and the
concomitant decline in insulin secretion.
– Pratley, Weyer, Hanson, Tataranni, Shuldiner, and Bogardus (2000)
Is Insulin Resistance a Cause or
Effect of Diabetes?
• Isolated insulin resistance is well tolerated in
transgenic animals and does not, by itself, lead
to diabetes.
• Beta cell abnormalities, on the other hand, do
predispose to overt diabetes in animal models.
• Isolated hyperinsulinemia can cause insulin
resistance just as well as insulin resistance can
cause hyperinsulinemia.
Caloric Excess
Technological advances have taken
away much of the activity in our
lives
• Fewer active jobs
• Greater reliance on motorised transport
• Energy-saving devices in the home, at work and
shopping environment
• Attractive and cheap home screen entertainment
CHALLENGE IS TO COUNTERACT
THESE EFFECTS
High-Tech increases Body Weight
Cellular phones and remote controls
deprive us from walking!
20 times daily x 20 m = 400 m
Walking distance lost/year
400x365 = 146,000 m
146 km = 25 h of walking
1 h of walking = 113-226 kcal
Energy saved =2800-6000 kcal
Rössner, 2002
 0.4-0.8 kg adipose tissue
Biological and cultural
mismatches to the modern
environment
FOOD
•
•
•
•
•
•
Strong signals to eat
Weak signals to stop
Increased availability
Eating is rewarding
No viable alternatives
Eating well is high
status
ACTIVITY
•
•
•
•
•
Weak activity signal
Strong signals to stop
Reduced availability
Inactivity is rewarding
Inactivity is a viable
alternative
• Inactivity is high status
The Evolution of Man
Since 1850
Daily Energy Expenditure in Primitive Hunter Gatherer -Farmers versus Sedentary Adults in USA
Machiguenga Indians in Peru
Kilocalories per Kilogram per Day
60
50
Men
Women
40
∆ = 42% ∆ = 27%
30
20
10
0
Primitive
Montgomery E., Fed Proceed 37:61-64, 1978
Modern
Denis Diderot - Pictorial Encyclopedia of Trades and Industry ( France 1740-1780)
“From the time of the Roman Conquest to the
time of the Civil War in the United States
(1860s), there was no improvement in the
efficiency in the movement of military troops
or supplies. This was changed by the use of
the steam engine to power ships and the
locomotive.”
The Men Who Dared:Building the
Transcontinental Railroad
Stephen Ambrose 2000
Decline in Daily Required Activity Resulting from
the Industrial Revolution
“Required daily activity” between 1850 and 1950 for
many people in technologically advancing societies
decreased substantially and this decrease was easily
observable.
Since the 1950s there has continued to be a decline in
“required daily activity” in many societies, but this
decrease in more subtle and less well documented.
Required Daily Activity High
for Many Workers 1n 1900
“ These lumberjacks worked
10-12 hours , six days per week
from April through November
logging the giant redwood
trees. Their primary equipment
included 9-pound axes, two-man
saws, buck saws, hand winches
and wedges.”
History of the Sierra Nevada
C. Taylor, 1996
WHO Obesity Guidelines, 2000
Technical Report Series 894
PAL = 1.0
RMR = 1Kcal/Kg/Hr (VO2 = 3.5 ml/kg/min)
50 kg body weight = 50 x 24 = 1200 Kcal/day
70 kg body weight = 70 x 24 = 1680 Kcal/day
100 kg body weight = 100 x 24 = 2400 Kcal/day
Physical Activity Level - PAL
Multiple of Resting Metabolic Rate
MEN
RMR
1.00
Very Light <1.46
Light
1.46 - 1.65
Moderate
1.66 - 1.90
Heavy
1.91 - 2.25
Exceptional >2.25
WOMEN
1.00
<1.41
1.41 - 1.55
1.56 - 1.75
1.76 - 2.05
>2.05
WHO Obesity Guidelines, 2000 - Technical Report Series 894
Variations in Energy Expenditure Due to Daily Physical Activity
* Kcal/day for 70 kg person
3
2.5
Light
Activity
2
1.5
Sedentary
RMR
WHO
GOAL
Finnish Lumberjacks
Primitive
Man
Very
Active
Moderately
Active
1
0.5
0
PAL
1.0
Kcal/day* 1680
1.30
2184
1.58
2644
1.75
2940
2.00
3360
2.65
4550
2.80
4800
Declines in on-the-job energy expenditure
during the past 50 years
Labor savings devices that decrease required energy expenditure
•
•
•
•
•
•
Computers
Electric typewriters
Electric calculators
Photocopy machines
Telefax machines
Telephones
• digital
• portable
• answering machines
• voice-mail
•
•
•
•
•
•
•
•
•
Satellites
Television
Video cameras and recorders
Robotics
Automated on-job equipment
Gas/electric home equipment
Microwave ovens
People movers - escalators
Wireless technology
Frequent Decreases in Short Bouts of Low
Intensity Activity Can Significantly
Alter Energy Balance Over 5 years
If 50 kilogram person exchanged walking
around office for sitting at computer for 5
minutes per hour, 8 hours per day, 5 days per
week, 50 weeks per year for 5 years = amount
of energy in 10.1 pounds or 4.6 kilogram body
fat.
Only 165 Kcal/week equal in energy to 10.1
pounds or 4.6 kilograms of body fat in 5 years
Technology and Inactivity - Future
Projections for further decline in energy expenditure in
the population due to continued decrease in daily
required physical activity over next two decades
Wireless Technology Likely to Decrease
Required Daily Activity
� Reduce commuting to work
� Computer to bank, shop, etc.
� More job tasks automated
� New technologies
Alan Greenspan - Chairman, Board of
Governors of the Federal Reserve System
The major cause for the continued increase in
the US economy without an increase in inflation
throughout the 1990s was an increase in
individual worker productivity.
It’ll cut down on the work breaks!
Individual worker productivity increased by:
• Working more hours - in 1998 US worker
averaged 1950 hours/year while European
workers average 1558 hours/year on-the-job:
25% more hours per year.
• Increase in worker efficiency by reducing
amount of physical movement time. Moving
around is a major cause of inefficiency for
computer & communications-based industry.
A Problem and challenge!
The US model used to increase economic
productivity is considered an approach to
be emulated by leaders in many developing
countries
MOSPA Study Population
Adults 25 - 65 Years
• WHO-MONICA project monitors global trends and
determinants of CVD
• MOSPA (MONICA Optional Study of Physical Activity)
questionnaire was developed to assess physical activity
behaviors of participating MONICA sites
• MOSPA data collected 1987-1994
• Beijing China (627 men, 575 women)
• Friuli Italy (700 men, 391 women)
• Warsaw Poland (535 men, 469 women)
Percent Time Spent by Adults in Different Categories of
Physical Activity in China, Italy, and Poland
% time
90
90
80
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
Occupational Household RecreationalTransportation
MEN
Data from WHO MONICA report, 2000
Occupational
China
Italy
Poland
Household
Recreational Transportation
WOMEN
Increased Time at Computer/TV/Video
Decreases Time for Leisure-Time
Physical Activity
>
Time Spent by USA Children Viewing Electronic Media
Hours/day
6
"The Media Generation"
5.2
5
2-7 years
8-18 years
4
2.8
3
2
1
0
TV
Video Tapes
Computer
Movies
TOTAL
Video
games
Kids and Media. A Kaiser Family Foundation Report, November 1999, Menlo Park, CA
National sample of 3,158 children in the USA
Why don’t you get off the computer and watch TV?
New Remote Control
Can Be Operated by
Remote
No more leaning forward to
get remote from coffee table
means greater convenience
for TV viewers.
Television watching became
even more convenient
with Sony’s introduction
of a new remote-controlled
remote control.
Technology and Leisure Activity
Potential reduction of leisure-time physical
activity as computer/communication
technology advances penetrate the masses
• Increased participation in computer games
• Increased use of computer as a communication
device for recreational purposes (chat rooms, etc.)
• Increased use of home-based video - including
video access on the internet
• Continued watching of television - cable, satellite
Physical Activity and Obesity
• Risk of overweight low if PAL is ≥ 1.75
A PAL of >1.75 is needed to prevent
“unhealthy weight gain” [based on results of 40
international studies]
• Prevalence of PAL ≤1.75 rapidly increasing in
developed and developing countries especially as they adopt computer and
communication technology.
WHO Obesity Guidelines, 2000 - Technical Report Series 894
Variations in Energy Expenditure Due to Daily Physical Activity
* Kcal/day for 70 kg person
3
2.5
Light
Activity
2
1.5
Sedentary
BMR
WHO
GOAL
Finnish Lumberjacks
Primitive
Man
Very
Active
Moderately
Active
1
0.5
0
PAL
1.0
Kcal/day* 1680
1.30
2184
1.58
2644
1.75
2940
2.00
3360
2.65
4550
2.80
4800
Variations in Energy Expenditure Due to Daily Physical Activity
3
* Kcal/day for 70 kg person
GOAL
2.5
2
Sedentary
1.5
Light
Activity
Moderately
Active
BMR
1
0.5
Finnish Lumberjacks
Primitive
Man
Very
Active
30 Min. Mod Intensity - USA (1995)
60 Min. Mod Intensity - Canada (2000) & IOM (2002)
0
PAL
1.0
Kcal/day* 1680
1.30
2184
1.52
2553
1.75
2940
2.00
3360
2.65
4550
2.80
4800
Variations in Energy Expenditure Due to Daily Physical Activity
3
* Kcal/day for 70 kg person
GOAL
2.5
2
1.5
Sedentary
Light
Activity
Moderately
Active
BMR
1
0.5
Finnish Lumberjacks
Primitive
Man
Very
Active
30 Min. Mod Intensity - USA (1995)
60 Min. Mod Intensity - Canada (2000)
0
+756 Kcal /day (WHO 2000)
PAL
1.0
Kcal/day* 1680
1.30
2184
1.52
2553
1.75
2940
2.00
3360
2.65
4550
2.80
4800
ACTIVITY INTERVAL!!
Factors Contributing to Recent Increases in Body
Mass in the USA & Other Developed Countries
Body Mass
Large portion size
High calorie
density
Low cost
Energy
Intake
Occupational
Transportation
Household
Energy
Expenditure
Sedentary
Recreational
?
Advances in Technology Throughout the Food Supply Chain
Has Reduced the Cost of High Calorie Low Nutrient Food
Low cost of increasing portion size (supersizing or value
marketing) is a major profit item for restaurants & fast
food markets
 7-Eleven Gulp to Double Gulp Coke Classis 37 cents buys
450 more calories (150 to 600 calories)
 Movie popcorn (unbuttered) - from small to large increases
cost by $1.31 but increases calories from 400 to 1160
 Cinnabon - Ordering a Cinnabon costs 48 cents more than a
Minibon but increases calories from 300 to 670

Advances in Technology Throughout the Food Supply Chain
Has Reduced the Cost of High Calorie Low Nutrient Food
 High calorie foods and drinks replacing low calorie items
 Starbucks Venti Coconut Crème Frappuccino “coffee” = 870 calories
 Adding “Value Meals” for single item orders
 Burger King Whopper ($2.24 & 680 calories) to Whopper Values
Meal - King ($4.80 & 1,710 calories
High Caloric Density Food
Always Available at Low Cost
CALORIES
Double Cheese Burger = 690
Super Size Coke =
280
Biggie Fries =
570
TOTAL =
1,540
62 grams of fat
Ad in Sports Illustrated 15/06/02
Introduction of New Larger Portions in the USA
70
Dinner plate diameter 25%
larger in 2000 vs. 1990
60
50
40
30
20
10
0
1970-74
1975-79
1980-84
Young & Nestle. AJPH,92:246, 2002
1985-89
1990-94
1995-99
McDonalds’ Worldwide Influence






28,000 restaurants worldwide - 2,000 new/year
Hire more than one million people per year
Largest private owner of real estate property in world
More $$ spent on advertising than any other US corp.
90% of children can identify Ronald McDonald - only
Santa Claus has higher recognition factor
The McDonald’s arches more widely recognized than
the Christian cross
FAST FOOD NATION - Eric Schlosser 2001
Obesity and sedentary living in
European adults
Martinez-Gonzalez et al. 1999, IJO, 23, 1192-1201
14
12
10
%
Obese 8
Men
Women
6
4
2
0
<15
15-20
21-25
26-35
>35
Hrs sat/wk
Hourly movement counts of obese and
non-obese adults: Weekdays
Cooper et al., EJCN, 2000
700
400.0
BMI<30
BMI>30
350.0
% BMI<30
300.0
% BMI>30
600
CSA counts.min -1
500
250.0
200.0
300
150.0
200
100
100.0
100
50
50.0
0
0.0
07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00
% participants
400
)
Hourly movement counts of obese and
non-obese subjects: Weekends
700
400.0
BMI<30
350.0
BMI>30
% BMI<30
300.0
% BMI>30
600
500
250.0
CSA counts.min -1
400
300
150.0
200
100
100.0
100
50
50.0
0
0.0
7:00
8:00
9:00
10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00
Tim e of day (hour from )
% participants
200.0
Eat to
Live!
Live to Eat!
“EAT TO LIVE”
Intake = Expenditure
Weight Stable
“LIVE TO EAT”
Intake > Expenditure
Obese
Ageing and Energy Expenditure
Intense
exercise
Sitting, coffee,
smoking
4000
Discretionary
Occupational
Dietary induced
thermogenesis
Basal metabolic
rate
3000
2000
1000
0
70 kg, Aged 25 years
James, Ralph and Ferro-Luzzi, 1989
70 kg, Aged 70 years
Fat as the Macronutrient Culprit
Protein
Carbohydrate
Fat
Energy content per g
4
4
9
Ability to end eating
High
Moderate
Low
Ability to suppress hunger
High
High
Low
Storage capacity
Low
Low
High
Pathway to transfer excess
to alternative compartment
Yes
Yes
No
Ability to stimulate own
oxidation
Excellent
Excellent
Poor
Adapted from WHO Consultation 1998
Dietary fat
Typical Belgian diet
Protein
15–20 %
Fat
40%
Carbohydrate
40–50%
Desired Belgian diet
Protein
15–20 %
Carbohydrate
45–55%
Fat
30%
Staessen L. et al. : Ann. Nutr. Metab. 1998; 42; 151-159
Energy needs
Measurement of Energy Intake
Contribution of fat, protein, carbohydrate and
alcohol to the energy intake in the average
British diet
Consequences of obesity
Stroke
Respiratory disease
Heart disease
Cardiovascular risk factors
Gallbladder disease
Diabetes
Hormonal abnormalities
Hyperuricaemia
and gout
Osteoarthritis
Cancer
Blindness in a child...
…because of fat infiltration
in eyelids...
Obesity : Definition
• APPLE TYPE :Central or abdominal
adiposity (ANDROID)  increased WHR
& associated with higher morbidity risk. ♂
>♀
Android obesity
or
Obesity : Definition
• PEAR TYPE : GYNOID or typical female
distribution of fat : less health risks
Gynoid obesity
or
visceral fat measurement using standard procedure at L5
Waist to hip circumferences
Correlates with visceral fat (Ashwell
et al, 1985
Coefficient of Variation in
measurement about 2%
WHO recommendations on
methdology
Epidemiological correlates with
obesity morbidity
Obesity : Definition
• WHR > 0.95 (♂) & > 0.80 (♀) : increased
health risk
Visceral Obesity and the Insulin
Resistance Syndrome
Insulin resistance and
hyperinsulinaemia
Hypertension
LVH
Congestive
heart failure
Glucose
intolerance
Excess visceral
abdominal adipose
tissue
Atherogenic dyslipidaemia
Total-C  LDL-C  HDL-C 
Triglycerides 
Small, dense LDL 
Apolipoprotein-B 
Prothrombotic state
PAI-1 
Factor VII 
Fibrinogen 
Metabolic Syndrome
Defined by ATP III (2001) as ≥ 3 of any of the following
 Waist circumference ≥ 102 cm in men and 88 cm in
women
 Triglyceride concentration ≥ 150 mg/dL (1.69 mmol/L
 HDL-C ≤ 40 mg/dL (1.04 mmol/L) in men and ≤ 50
mg/dL (1.29 mmol/L) in women
 Blood pressure ≥ 130/85 mm Hg
 Blood glucose ≥ 110 mg/dL (6.1 mmol/L)
Prevalence of Metabolic Syndrome in Men and WOMEN - USA
45
MEN (24.0%)
WOMEN (23.4%)
40
35
Mexican American = 31.9%
30
Total = 47 million people
NHANES - 1994
25
20
15
10
5
0
20-29
30-39
40-49
50-59
AGE -YEARS
60-69
70+
Obesity treatment
Why?
• Obesity is a chronic condition
• Associated with co-morbidities
–Type 2 diabetes
–Arthritis
• Associated with risk factors
–Hypertension
–Dislipidaemia
–Coronary heart disease
• Imposes a substantial economic burden
Age-adjusted CHD
incidence/100 000 person-years
Abdominal Adiposity Increases
CHD Risk Independently of BMI
128
140
120
100
80
60
40
20
0
110
106
97 83
89
77
46
High
(25.2)
Waist
Circumference
tertiles (cm)
55
High (81.8)
Medium (73.7-81.7)
Low (73.6)
Medium
Low
(22.2-25.1) (22.1)
BMI tertiles (kg/m2)
Rexrode KM et al. JAMA, 1998; 280: 1843-8
Health consequences of obesity
 Cardiovascular disease
 Sleep apnoea
 Type 2 diabetes
 Degenerative joint disease
 Hypertension
 Some types of cancer
 Dyslipidaemia
 Gallstones
 Ischaemic stroke
 Gynaecologic irregularities
Clinical guidelines. National Heart, Lung, and Blood Institute Web site. Available at:
http://www.nhlbi.nih.gov/nhlbi/cardio/obes/prof/guidelns/ob_gdlns.htm. Accessed July 31, 1998.
Relative risk of health problems
associated with obesity
Greatly Increased
(relative risk >>3)
Moderately increased
(relative risk c. 2-3)
Slightly increased
(relative risk c. 1-2)
Diabetes
Coronary heart disease
postmenopausal women,
Gall bladder disease
Hypertension
abnormalities
Osteoarthritis (knees)
Hyperuricaemia and gout
Cancer (breast cancer in
endometrial cancer,
colon cancer)
Reproductive hormone
Dyslipidaemia
Insulin resistance
Breathlessness
Sleep apnoea
from maternal obesity
Polycystic ovary syndrome
Impaired fertility
Fetal defects arising
Low back pain
Increased anaesthetic risk
IOTF Report
Proportion of disease prevalence
attributable to obesity
Type 2 diabetes
57%
Hypertension
17%
Coronary heart disease
17%
Gallbladder disease
30%
Osteoarthritis
14%
Breast cancer
11%
Uterine cancer
11%
Colon cancer
11%
Wolf et al. Obes Res. 1998;6:97-106.
Obesity related cardiovascular and
renal risk
• Obesity is a independent risk factor for the
development of CV and Renal disease, even
in the absence of other pathologies
Burden of Disease
• Burden of disease analysis gives a unique
perspective on health. Fatal and non-fatal outcomes
are integrated, but can be examined separately as
well.
• YLL - Years of Life Lost due to premature mortality
• +YDL - Years of Life Lost due to Disability
• DALY Disability Adjusted Life Years
•
one DALY is one lost year of ‘healthy’ life
Risk Factor
• A condition, physical characteristic, or
behavior that increases the probability (the
risk) that a currently healthy individual will
develop a particular disease.
• Types of risks factors:
– Environmental
– Behavioral
– Social
– Genetic
Lifestyle Diseases and Risk
Factors
•
•
•
•
Diabetes
Hypertension
Heart Disease
Cancer
•
•
•
•
•
•
Genetic
Obesity
Eating Patterns
Physical Activity
Smoking
Urbanisation
Coronary Heart Disease
• Major risk factors
– High Total Cholesterol or LDL, Low HDL
– Elevated Homocysteine (low folate intake)
– Hypertension
– Cigarette Smoking
– Obesity
– Diabetes Mellitus
– Sedentary Lifestyle
– Excessive Alcohol
Factors which Influence Blood
Lipid Levels
• Detrimental effect
–
–
–
–
–
Saturated fat
Trans fatty acids
Dietary cholesterol
Diabetes
Obesity
• central abdominal
• Obesity
• Sedentary Lifestyle
• Beneficial effect
– Vegetables and fruits
– Polyunsaturated fatty acids
– Monounsaturated fatty
acids
– Omega 3 fatty acids
– Dietary fibre
– Moderate alcohol
– Physical activity
Risk Factors for Hypertension
Detrimental effect
• Age
• Gender
• Smoking
• Obesity
• Sodium
• Alcohol
• Stress
Beneficial effect
• Potassium
• Omega -3 fatty acids
• Physical activity
Health Agencies’
Recommendations for Prevention
of Hypertension
•
•
•
•
•
Smoking cessation
Reduce weight
Reduce salt
Moderate alcohol
Reduce fat
• Increase fruit and
vegetables
• Regular fish
consumption
• Increase physical
activity
Risk Factors for Diabetes
• Genetic
• Age
• Gender
•
•
•
•
•
•
Obesity
Eating pattern
Physical Activity
Hypertension
Gestational Diabetes
Urbanisation
Trend in Prevalence of Obesity*:
NHANES Data
36
US Population (%)
34
32
30
28
26
24
22
20
NHES (19601962)
NHANES I
(1971-1974)
NHANES II
(1976-1980)
NHANES IIIb
(1988-1994)
*BMI  27.3 mg/m2 for women;  27.8 kg/m2 for men
Kuczmarski RJ, et al. JAMA. 1994;272:205-211.
Type 2 Diabetes in the Pediatric Population:
First Nation Data
New Diabetes Patients
Referred to Clinic
20
15
10
5
0
'86
'87
'88
'89
'90
'91
'92 '93
Year
Dean HJ. Diabetes. 1999;48(suppl 1):A168. Abstract 0730.
Adapted with permission from the American Diabetes Association.
'94
'95
'96
'97
'98
Prevalence of impaired glucose tolerance
among children and adolescents with marked
obesity
Sinha R, Fish G et al.
NEJM 2002; 346: 802-10
– Aim
• Determine the prevalence of IGT in a multiethnical cohort of 167
children and adolescents
• OGTT with glucose, insulin, C-peptide
Prevalence of impaired glucose tolerance
among children and adolescents with marked
obesity
Sinha R, Fish G et al.
Results
•
•
•
•
25 % IGT in children (4-10y)
21 % IGT in adolescents (11-18y)
Increased insulin values in IGT
4 % insidous DM2 in adolescents
NEJM 2002; 346: 802-10
Prevalence of impaired glucose tolerance
among children and adolescents with marked
obesity
Sinha R, Fish G et al.
NEJM 2002; 346: 802-10
– Conclusion
• High prevalence of IGT in children and adolescents with obesity
– > 95 percentile age and sex.
• Ethnicity not important
• IGT accompanied by insulin resistance with adequate -cell
function
• DM2 accompanied by insulin deficiency indicative of -cell
failure
Age-Adjusted Relative Risk
Link Between Obesity and Type 2 Diabetes:
Nurses’ Health Study
120
100
80
60
40
20
0
< 22
2222.9
2323.8
2424.9
2526.9
2728.9
BMI (kg/m2)
Colditz GA, et al. Ann Intern Med. 1995;122:481-486.
2930.9
3132.9
3334.9
> 35
Obesity is a risik factor for type 2
diabetes
Age-adjusted
relative risk of type 2 diabetes
100
90
80
70
60
50
Males
Females
40
30
20
10
0
<22
<23
2323,9
2424,9
2526,9
2728,9
2930,9
3132,9
33- >=35
34,9
Adapted from Chan JM et al. Diabetes Care 1994; 17: 961-9
Colditz et al. Ann Intern Med 1995; 122: 481-6
a
Adapted from Chan JM et al. Diabetes Care 1994; 17: 961-9
Link Between Obesity and Type 2 Diabetes:
Nurses’ Health Study
80
Loss of 5-10 kg
Age-Adjusted Relative Risk
70
Loss or gain of 4.9 kg or less
Gain of 5-6.9 kg
60
50
Gain of 7-10.9 kg
Gain of 11-19.9 kg
Gain of 20 kg or more
40
30
20
10
0
<22.0
22.0-24.9
25.0-28.9
BMI (kg/m2) at Age 18 Years
Colditz GA, et al. Ann Intern Med. 1995;122:481-486.
29+
Diet, lifestyle and the risk of type 2 diabetes
mellitus in women
Hu FB, Manson JE et al.
NEJM, 2001; 345:790-7
– Risk factors for type 2 diabetes
•
•
•
•
obesity en weight gain
Physical inactivity, independent of obesity
Low fibre and high GI diet
Specific FA
– Aim
• Study the combined effect of these factors
Diet, lifestyle and the risk of type 2 diabetes
mellitus in women
Hu FB, Manson JE et al.
NEJM, 2001; 345:790-7
– Study population
• Nurses’ Health Study from 1980-1996
• 89 941 patients of total 121 700
• Exclusion diabetes, cancer and CV disease
– Dietary-Interview
• questionnaire 61 items, semi-quantitive
• each diet factor: score 1-5 for the 4 nutrients, dependent
on quintile intake
Diet, lifestyle and the risk of type 2 diabetes
mellitus in women
Hu FB, Manson JE et al.
NEJM, 2001; 345:790-7
– Investigation of non-nutrition related factors
•
•
•
•
•
Smoking
Menopausal status/substitution
Body weight
Physical activity
Family history of diabetes
Diet, lifestyle and the risk of type 2 diabetes
mellitus in women
Hu FB, Manson JE et al.
NEJM, 2001; 345:790-7
– Defining low-risk group (LRG):
•
•
•
•
•
BMI<25 kg/m2
Physical activity :30 min/d moderate activity
Smoker : Non-Smoker
alcohol: 0.5U/d
diet: Little trans fat, low glycemic index, high fibre intake,
High ration PUFA
Diet, lifestyle and the risk of type 2 diabetes
mellitus in women
Hu FB, Manson JE et al.
NEJM, 2001; 345:790-7
– 16 year follow-up
– diagnose DM according National Diabetes Data Group
– Relative risks calculated :
incidence of diabetes in LRG
incidence diabetes amongst rest of the women
– ‘population attributable risk’
Estimation of the percentage of diabetes type 2 which would
not occur if all women were to be placed in the LRG.
Most important
risk factor !
61% of new cases
DM result of
overweight
87 % new cases
preventable if all
women placed in
LRG
NEJM 2001, 345:790-797
• Conclusion
– combination of different factors can prevent Diabetes
•
•
•
•
•
BMI  25
Diet : high fibre intake; PUFA, Low SFA; trans fats and GI
Regular physiacl activity
Non Smoker
Moderate alcohol use
– incidence of diabetes approx. 90 % lower in this group
– Behavior changes can prevent diabetes
– Most important determinant for DM 2
• OVERWEIGHT
BUT
Present prevalence still increasing
Current therapy strategies not sufficient
– Education Necessary
Risk Factors for Cancers
•
•
•
•
•
•
Cigarettes/Tobacco
Betel Nut (lime?)
Hepatitis B
Obesity
Hyperglycaemia
Physical Activity
• Dietary Factors
– Fat
– Fibre
– Meat (cooking
methods)
– Alcohol
– Vegetables and Fruits
– Omega 3 fatty acids
Can Johnny come out and eat?
Can physical activity prevent
weight gain?
Attenuated weight gain with
recreational physical activity: MEN
Baseline weight gain of inactive
0
Walking
Cycling
Golf
Running
-26
26-39
40-54
Age group
55+
NHANES Study, USA
Prospective studies on the effect of
physical activity/fitness on long term
weight gain.
• DiPietro et al. 1998 7 yrs *men, *women
• Coakley et al. 1998 4 yrs *men
• Lewis et al. 1998
7 yrs *men, *women
• Williamson et al. 1993 10 yrs *men, *women
• Rissanen et al. 1991 5 yrs *men, *women
Estimated relative odds of weight
gain category by recreational
physical activity: WOMEN
BaseWeight gain category
Follow-up
3-8 kg
8-13 kg
Hi - Hi
1.0
1.0
Med-Med 1.7
1.0
Lo - Lo
2.1
1.5
Increased 1.7
0.9
Decreased 2.4
1.3
>13 kg
1.0
3.4
7.1
3.4
6.2
Williamson et al., (1993), IJO, 17, 279-86
Effects of an Obesity Prevention and Exercise Program
on the Development of NIDDM in Men and Women
with Impaired Glucose Tolerance
Percent of Participants Free of Diabetes
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Control
Lifestyle
P <0.001
80%
58%
Year Year Year Year Year Year
1
2
3
4
5
6
Tuomilehto, et al. NEJM 344:1343-1350, 2001
Effects of Metformin or Lifestyle Interventions on the
Incidence of Developing Diabetes in High Risk Men and Women
Cases per 100 person-years
14
12
10
8
6
4
2
0
Placebo
Metformin
Lifestyle
N = 3234
Men & women
• Overweight
• Sedentary
• High glucose
PA = 150 min/w
Weight - 12 lbs.
Metformin =
850 mg 2 x day
2.8 yr. follow-up
ALL
Men
Women
Diabetes Prevention Program Research Group.NEJM,2002:346:393-403
Reversal of Downward Trend in Daily Physical Activity
Will Require Innovative and Integrated Approaches
Recent natural gas and
electric energy shortage
may be our salvation in
California.
Eco House at Humbolt
State University generates
all its power needs via
human power generation
using cycle ergometers
connected to generators.
Integrated Programs to Reduce Obesity
 Public education via mass media - “set the stage”
 Community-based programs for physical activity and
nutrition - promote individual behavior change
 Environmental change to promote activity - sidewalks,
parks, showers @worksites, mall walking, etc.
 Policy change to promote activity and healthy eating schools (PE & recess), worksites, government, etc.
 Incentive/penalty programs - health insurance
companies: third-party payment can be a disincentive
Spectrum of obesity management
Weight loss has
beneficial health effects
A weight loss of  5% in obese individuals with
comorbid type 2 diabetes, hypertension or
dyslipidaemia resulted in:
•
•
•
•
Improved glycaemic control
Reduced blood pressure
Improved lipid profile
20% reduction in premature mortality in
overweight women with obesity-related health
conditions
Goldstein DJ. Int J Obesity, 1991
Obesity management:
objectives
•
•
•
•
•
•
•
Promotion of weight loss
Long-term weight maintenance
Long-term prevention of weight gain
Improvement of risk factors
Encouragement of active lifestyle
Improvement in quality of life
Change in eating patterns
THE MANAGEMENT OF OBESITY:
AN INTEGRATED APPROACH
• Obesity is a serious medical condition requiring
long-term management
• Management needs to be flexible and integrate
different therapeutic approaches according to
individual patient needs including
– Dietary management
– Lifestyle modification
– Physical activity
– Drug therapy
– Surgery
WEIGHT MANAGEMENT
Weight
Weight Gain
Keep Weight
Slight Reduction
Moderate Red.
(medical useful)
Obesity
Overweight
Normal
Weight
Normalising Weight
(Not realistic and
contraproductive)
Years
PATIENT EXPECTATIONS
Patient weight
loss goals
% patient achieved
after intervention
Dream weight
-38%
0%
Happy weight
-31%
9%
Acceptable weight
-25%
24%
Dissappointing weight
-17%
20%
Below dissappointing weight
Reference: Foster et al. J Consult Clin Psych 1997; 65(1): 79-81
47%
CONTRASTING PATIENT AND
PHYSICIAN EXPECTATIONS
Expectation
Rate of weight
loss
Weight loss (% of
initial weight)
Time on diet
Goals
Patient
Physician
Rapid
Gradual
20%
5-10% (15%)
Some weeks
Rest of life
Weight loss
Cosmetic
purposes
Physical fitness
Weight maintenance
To decrease obesity co-morbidities
Metabolic fitness
Reference: Ziegler O, Meyer L, Guerci B et al. In press.
And finally, we need to recognize that
we do not know how to successfully
“treat” obesity…
The question we need to address is:
How do we help people maintain
health in an environment conducive
to people weighing more?
THE NEED FOR REALISTIC GOALS IN
OBESITY MANAGEMENT
• Shift focus from changing appearance to improving health
• Consider healthier weight over time - not ideal weight
• Sustained moderate weight loss of 5-10kg
(5-10% of initial body weight)
–
Elevated BP
–
Blood sugar concentrations
–
Serum triglycerides
–
HDL-cholesterol levels
Long-term management of obesity
• Efficacy of long-term treatment requires
– Patient motivation for weight loss
– Patient satisfaction with weight loss
– Patient satisfaction with treatment
• Best achieved by combination of
– Low-fat diet
– Increased physical activity
– Well-tolerated pharmacotherapy